Day1

Check the original database

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db "SELECT count(DISTINCT username) FROM sample2bioinformatician;"

count(DISTINCT username)
------------------------
26                      

cd /shared/projects/2314_medbioinfo/hui/MedBioinfo23

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

mkdir analyses/blastn & cd analyses/blastn

[1] 53695
bash: cd: analyses/blastn: No such file or directory

cd analyses/blastn

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

BLASTn of mini reads subsets versus refseq viral database

module load blast

makeblastdb --help

USAGE
  makeblastdb [-h] [-help] [-in input_file] [-input_type type]
    -dbtype molecule_type [-title database_title] [-parse_seqids]
    [-hash_index] [-mask_data mask_data_files] [-mask_id mask_algo_ids]
    [-mask_desc mask_algo_descriptions] [-gi_mask]
    [-gi_mask_name gi_based_mask_names] [-out database_name]
    [-blastdb_version version] [-max_file_sz number_of_bytes]
    [-logfile File_Name] [-taxid TaxID] [-taxid_map TaxIDMapFile] [-version]

DESCRIPTION
   Application to create BLAST databases, version 2.12.0+

Use '-help' to print detailed descriptions of command line arguments
========================================================================

Error: Unknown argument: "-help"
Error:  (CArgException::eInvalidArg) Unknown argument: "-help"

cd MedBioinfo23

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

mkdir ../data/blast_db

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

cd MedBioinfo23

zcat /shared/projects/2314_medbioinfo/refseq/viral.genomic.fna.gz | makeblastdb -dbtype nucl -title Refseq_viral_genome -out data/blast_db/refseq_viral_genomic/

Building a new DB, current time: 05/29/2023 11:28:39
New DB name:   /shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/data/blast_db/refseq_viral_genomic
New DB title:  Refseq_viral_genome
Sequence type: Nucleotide
Keep MBits: T
Maximum file size: 1000000000B
Adding sequences from FASTA; added 14813 sequences in 7.82641 seconds.

blastdbcmd -info -db data/blast_db/refseq_viral_genomic

Database: Refseq_viral_genome
	14,813 sequences; 469,589,088 total bases

Date: May 29, 2023  11:28 AM	Longest sequence: 2,473,870 bases

BLASTDB Version: 5

Volumes:
	/shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/data/blast_db/refseq_viral_genomic

blastn -help

USAGE
  blastn [-h] [-help] [-import_search_strategy filename]
    [-export_search_strategy filename] [-task task_name] [-db database_name]
    [-dbsize num_letters] [-gilist filename] [-seqidlist filename]
    [-negative_gilist filename] [-negative_seqidlist filename]
    [-taxids taxids] [-negative_taxids taxids] [-taxidlist filename]
    [-negative_taxidlist filename] [-entrez_query entrez_query]
    [-db_soft_mask filtering_algorithm] [-db_hard_mask filtering_algorithm]
    [-subject subject_input_file] [-subject_loc range] [-query input_file]
    [-out output_file] [-evalue evalue] [-word_size int_value]
    [-gapopen open_penalty] [-gapextend extend_penalty]
    [-perc_identity float_value] [-qcov_hsp_perc float_value]
    [-max_hsps int_value] [-xdrop_ungap float_value] [-xdrop_gap float_value]
    [-xdrop_gap_final float_value] [-searchsp int_value]
    [-sum_stats bool_value] [-penalty penalty] [-reward reward] [-no_greedy]
    [-min_raw_gapped_score int_value] [-template_type type]
    [-template_length int_value] [-dust DUST_options]
    [-filtering_db filtering_database]
    [-window_masker_taxid window_masker_taxid]
    [-window_masker_db window_masker_db] [-soft_masking soft_masking]
    [-ungapped] [-culling_limit int_value] [-best_hit_overhang float_value]
    [-best_hit_score_edge float_value] [-subject_besthit]
    [-window_size int_value] [-off_diagonal_range int_value]
    [-use_index boolean] [-index_name string] [-lcase_masking]
    [-query_loc range] [-strand strand] [-parse_deflines] [-outfmt format]
    [-show_gis] [-num_descriptions int_value] [-num_alignments int_value]
    [-line_length line_length] [-html] [-sorthits sort_hits]
    [-sorthsps sort_hsps] [-max_target_seqs num_sequences]
    [-num_threads int_value] [-mt_mode int_value] [-remote] [-version]

DESCRIPTION
   Nucleotide-Nucleotide BLAST 2.12.0+

OPTIONAL ARGUMENTS
 -h
   Print USAGE and DESCRIPTION;  ignore all other parameters
 -help
   Print USAGE, DESCRIPTION and ARGUMENTS; ignore all other parameters
 -version
   Print version number;  ignore other arguments

 *** Input query options
 -query <File_In>
   Input file name
   Default = `-'
 -query_loc <String>
   Location on the query sequence in 1-based offsets (Format: start-stop)
 -strand <String, `both', `minus', `plus'>
   Query strand(s) to search against database/subject
   Default = `both'

 *** General search options
 -task <String, Permissible values: 'blastn' 'blastn-short' 'dc-megablast'
                'megablast' 'rmblastn' >
   Task to execute
   Default = `megablast'
 -db <String>
   BLAST database name
    * Incompatible with:  subject, subject_loc
 -out <File_Out>
   Output file name
   Default = `-'
 -evalue <Real>
   Expectation value (E) threshold for saving hits 
   Default = `10'
 -word_size <Integer, >=4>
   Word size for wordfinder algorithm (length of best perfect match)
 -gapopen <Integer>
   Cost to open a gap
 -gapextend <Integer>
   Cost to extend a gap
 -penalty <Integer, <=0>
   Penalty for a nucleotide mismatch
 -reward <Integer, >=0>
   Reward for a nucleotide match
 -use_index <Boolean>
   Use MegaBLAST database index
   Default = `false'
 -index_name <String>
   MegaBLAST database index name (deprecated; use only for old style indices)

 *** BLAST-2-Sequences options
 -subject <File_In>
   Subject sequence(s) to search
    * Incompatible with:  db, gilist, seqidlist, negative_gilist,
   negative_seqidlist, taxids, taxidlist, negative_taxids, negative_taxidlist,
   db_soft_mask, db_hard_mask
 -subject_loc <String>
   Location on the subject sequence in 1-based offsets (Format: start-stop)
    * Incompatible with:  db, gilist, seqidlist, negative_gilist,
   negative_seqidlist, taxids, taxidlist, negative_taxids, negative_taxidlist,
   db_soft_mask, db_hard_mask, remote

 *** Formatting options
 -outfmt <String>
   alignment view options:
     0 = Pairwise,
     1 = Query-anchored showing identities,
     2 = Query-anchored no identities,
     3 = Flat query-anchored showing identities,
     4 = Flat query-anchored no identities,
     5 = BLAST XML,
     6 = Tabular,
     7 = Tabular with comment lines,
     8 = Seqalign (Text ASN.1),
     9 = Seqalign (Binary ASN.1),
    10 = Comma-separated values,
    11 = BLAST archive (ASN.1),
    12 = Seqalign (JSON),
    13 = Multiple-file BLAST JSON,
    14 = Multiple-file BLAST XML2,
    15 = Single-file BLAST JSON,
    16 = Single-file BLAST XML2,
    17 = Sequence Alignment/Map (SAM),
    18 = Organism Report
   
   Options 6, 7, 10 and 17 can be additionally configured to produce
   a custom format specified by space delimited format specifiers,
   or in the case of options 6, 7, and 10, by a token specified
   by the delim keyword. E.g.: "17 delim=@ qacc sacc score".
   The delim keyword must appear after the numeric output format
   specification.
   The supported format specifiers for options 6, 7 and 10 are:
   	    qseqid means Query Seq-id
   	       qgi means Query GI
   	      qacc means Query accesion
   	   qaccver means Query accesion.version
   	      qlen means Query sequence length
   	    sseqid means Subject Seq-id
   	 sallseqid means All subject Seq-id(s), separated by a ';'
   	       sgi means Subject GI
   	    sallgi means All subject GIs
   	      sacc means Subject accession
   	   saccver means Subject accession.version
   	   sallacc means All subject accessions
   	      slen means Subject sequence length
   	    qstart means Start of alignment in query
   	      qend means End of alignment in query
   	    sstart means Start of alignment in subject
   	      send means End of alignment in subject
   	      qseq means Aligned part of query sequence
   	      sseq means Aligned part of subject sequence
   	    evalue means Expect value
   	  bitscore means Bit score
   	     score means Raw score
   	    length means Alignment length
   	    pident means Percentage of identical matches
   	    nident means Number of identical matches
   	  mismatch means Number of mismatches
   	  positive means Number of positive-scoring matches
   	   gapopen means Number of gap openings
   	      gaps means Total number of gaps
   	      ppos means Percentage of positive-scoring matches
   	    frames means Query and subject frames separated by a '/'
   	    qframe means Query frame
   	    sframe means Subject frame
   	      btop means Blast traceback operations (BTOP)
   	    staxid means Subject Taxonomy ID
   	  ssciname means Subject Scientific Name
   	  scomname means Subject Common Name
   	sblastname means Subject Blast Name
   	 sskingdom means Subject Super Kingdom
   	   staxids means unique Subject Taxonomy ID(s), separated by a ';'
   			 (in numerical order)
   	 sscinames means unique Subject Scientific Name(s), separated by a ';'
   	 scomnames means unique Subject Common Name(s), separated by a ';'
   	sblastnames means unique Subject Blast Name(s), separated by a ';'
   			 (in alphabetical order)
   	sskingdoms means unique Subject Super Kingdom(s), separated by a ';'
   			 (in alphabetical order) 
   	    stitle means Subject Title
   	salltitles means All Subject Title(s), separated by a '<>'
   	   sstrand means Subject Strand
   	     qcovs means Query Coverage Per Subject
   	   qcovhsp means Query Coverage Per HSP
   	    qcovus means Query Coverage Per Unique Subject (blastn only)
   When not provided, the default value is:
   'qaccver saccver pident length mismatch gapopen qstart qend sstart send
   evalue bitscore', which is equivalent to the keyword 'std'
   The supported format specifier for option 17 is:
   	        SQ means Include Sequence Data
   	        SR means Subject as Reference Seq
   Default = `0'
 -show_gis
   Show NCBI GIs in deflines?
 -num_descriptions <Integer, >=0>
   Number of database sequences to show one-line descriptions for
   Not applicable for outfmt > 4
   Default = `500'
    * Incompatible with:  max_target_seqs
 -num_alignments <Integer, >=0>
   Number of database sequences to show alignments for
   Default = `250'
    * Incompatible with:  max_target_seqs
 -line_length <Integer, >=1>
   Line length for formatting alignments
   Not applicable for outfmt > 4
   Default = `60'
 -html
   Produce HTML output?
 -sorthits <Integer, (>=0 and =<4)>
   Sorting option for hits:
   alignment view options:
     0 = Sort by evalue,
     1 = Sort by bit score,
     2 = Sort by total score,
     3 = Sort by percent identity,
     4 = Sort by query coverage
   Not applicable for outfmt > 4
 -sorthsps <Integer, (>=0 and =<4)>
   Sorting option for hps:
     0 = Sort by hsp evalue,
     1 = Sort by hsp score,
     2 = Sort by hsp query start,
     3 = Sort by hsp percent identity,
     4 = Sort by hsp subject start
   Not applicable for outfmt != 0

 *** Query filtering options
 -dust <String>
   Filter query sequence with DUST (Format: 'yes', 'level window linker', or
   'no' to disable)
   Default = `20 64 1'
 -filtering_db <String>
   BLAST database containing filtering elements (i.e.: repeats)
 -window_masker_taxid <Integer>
   Enable WindowMasker filtering using a Taxonomic ID
 -window_masker_db <String>
   Enable WindowMasker filtering using this repeats database.
 -soft_masking <Boolean>
   Apply filtering locations as soft masks
   Default = `true'
 -lcase_masking
   Use lower case filtering in query and subject sequence(s)?

 *** Restrict search or results
 -gilist <String>
   Restrict search of database to list of GIs
    * Incompatible with:  seqidlist, taxids, taxidlist, negative_gilist,
   negative_seqidlist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -seqidlist <String>
   Restrict search of database to list of SeqIDs
    * Incompatible with:  gilist, taxids, taxidlist, negative_gilist,
   negative_seqidlist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -negative_gilist <String>
   Restrict search of database to everything except the specified GIs
    * Incompatible with:  gilist, seqidlist, taxids, taxidlist,
   negative_seqidlist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -negative_seqidlist <String>
   Restrict search of database to everything except the specified SeqIDs
    * Incompatible with:  gilist, seqidlist, taxids, taxidlist,
   negative_gilist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -taxids <String>
   Restrict search of database to include only the specified taxonomy IDs
   (multiple IDs delimited by ',')
    * Incompatible with:  gilist, seqidlist, taxidlist, negative_gilist,
   negative_seqidlist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -negative_taxids <String>
   Restrict search of database to everything except the specified taxonomy IDs
   (multiple IDs delimited by ',')
    * Incompatible with:  gilist, seqidlist, taxids, taxidlist,
   negative_gilist, negative_seqidlist, negative_taxidlist, remote, subject,
   subject_loc
 -taxidlist <String>
   Restrict search of database to include only the specified taxonomy IDs
    * Incompatible with:  gilist, seqidlist, taxids, negative_gilist,
   negative_seqidlist, negative_taxids, negative_taxidlist, remote, subject,
   subject_loc
 -negative_taxidlist <String>
   Restrict search of database to everything except the specified taxonomy IDs
    * Incompatible with:  gilist, seqidlist, taxids, taxidlist,
   negative_gilist, negative_seqidlist, negative_taxids, remote, subject,
   subject_loc
 -entrez_query <String>
   Restrict search with the given Entrez query
    * Requires:  remote
 -db_soft_mask <String>
   Filtering algorithm ID to apply to the BLAST database as soft masking
    * Incompatible with:  db_hard_mask, subject, subject_loc
 -db_hard_mask <String>
   Filtering algorithm ID to apply to the BLAST database as hard masking
    * Incompatible with:  db_soft_mask, subject, subject_loc
 -perc_identity <Real, 0..100>
   Percent identity
 -qcov_hsp_perc <Real, 0..100>
   Percent query coverage per hsp
 -max_hsps <Integer, >=1>
   Set maximum number of HSPs per subject sequence to save for each query
 -culling_limit <Integer, >=0>
   If the query range of a hit is enveloped by that of at least this many
   higher-scoring hits, delete the hit
    * Incompatible with:  best_hit_overhang, best_hit_score_edge
 -best_hit_overhang <Real, (>0 and <0.5)>
   Best Hit algorithm overhang value (recommended value: 0.1)
    * Incompatible with:  culling_limit
 -best_hit_score_edge <Real, (>0 and <0.5)>
   Best Hit algorithm score edge value (recommended value: 0.1)
    * Incompatible with:  culling_limit
 -subject_besthit
   Turn on best hit per subject sequence
 -max_target_seqs <Integer, >=1>
   Maximum number of aligned sequences to keep 
   (value of 5 or more is recommended)
   Default = `500'
    * Incompatible with:  num_descriptions, num_alignments

 *** Discontiguous MegaBLAST options
 -template_type <String, `coding', `coding_and_optimal', `optimal'>
   Discontiguous MegaBLAST template type
    * Requires:  template_length
 -template_length <Integer, Permissible values: '16' '18' '21' >
   Discontiguous MegaBLAST template length
    * Requires:  template_type

 *** Statistical options
 -dbsize <Int8>
   Effective length of the database 
 -searchsp <Int8, >=0>
   Effective length of the search space
 -sum_stats <Boolean>
   Use sum statistics

 *** Search strategy options
 -import_search_strategy <File_In>
   Search strategy to use
    * Incompatible with:  export_search_strategy
 -export_search_strategy <File_Out>
   File name to record the search strategy used
    * Incompatible with:  import_search_strategy

 *** Extension options
 -xdrop_ungap <Real>
   X-dropoff value (in bits) for ungapped extensions
 -xdrop_gap <Real>
   X-dropoff value (in bits) for preliminary gapped extensions
 -xdrop_gap_final <Real>
   X-dropoff value (in bits) for final gapped alignment
 -no_greedy
   Use non-greedy dynamic programming extension
 -min_raw_gapped_score <Integer>
   Minimum raw gapped score to keep an alignment in the preliminary gapped and
   traceback stages
 -ungapped
   Perform ungapped alignment only?
 -window_size <Integer, >=0>
   Multiple hits window size, use 0 to specify 1-hit algorithm
 -off_diagonal_range <Integer, >=0>
   Number of off-diagonals to search for the 2nd hit, use 0 to turn off
   Default = `0'

 *** Miscellaneous options
 -parse_deflines
   Should the query and subject defline(s) be parsed?
 -num_threads <Integer, >=1>
   Number of threads (CPUs) to use in the BLAST search
   Default = `1'
    * Incompatible with:  remote
 -mt_mode <Integer, (>=0 and =<1)>
   Multi-thread mode to use in BLAST search:
    0 (auto) split by database 
    1 split by queries
   Default = `0'
    * Requires:  num_threads
 -remote
   Execute search remotely?
    * Incompatible with:  gilist, seqidlist, taxids, taxidlist,
   negative_gilist, negative_seqidlist, negative_taxids, negative_taxidlist,
   subject_loc, num_threads

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

module load seqkit

seqkit stats data/merged_pairs/*.fastq.gz

file                                                       format  type  num_seqs     sum_len  min_len  avg_len  max_len
data/merged_pairs/ERR6913156.flash.extendedFrags.fastq.gz  FASTQ   DNA     22,291   3,262,339       35    146.4      292
data/merged_pairs/ERR6913156.flash.notCombined_1.fastq.gz  FASTQ   DNA      1,867     280,159       35    150.1      151
data/merged_pairs/ERR6913156.flash.notCombined_2.fastq.gz  FASTQ   DNA      1,867     280,159       35    150.1      151
data/merged_pairs/ERR6913158.flash.extendedFrags.fastq.gz  FASTQ   DNA    690,579  99,890,771       35    144.6      292
data/merged_pairs/ERR6913158.flash.notCombined_1.fastq.gz  FASTQ   DNA     65,028   9,760,304       35    150.1      151
data/merged_pairs/ERR6913158.flash.notCombined_2.fastq.gz  FASTQ   DNA     65,028   9,759,131       35    150.1      151
data/merged_pairs/ERR6913168.flash.extendedFrags.fastq.gz  FASTQ   DNA     63,620   9,531,276       35    149.8      292
data/merged_pairs/ERR6913168.flash.notCombined_1.fastq.gz  FASTQ   DNA      7,711   1,158,275       35    150.2      151
data/merged_pairs/ERR6913168.flash.notCombined_2.fastq.gz  FASTQ   DNA      7,711   1,158,282       35    150.2      151
data/merged_pairs/ERR6913169.flash.extendedFrags.fastq.gz  FASTQ   DNA     76,719  11,359,696       35    148.1      292
data/merged_pairs/ERR6913169.flash.notCombined_1.fastq.gz  FASTQ   DNA      6,522     978,887       35    150.1      151
data/merged_pairs/ERR6913169.flash.notCombined_2.fastq.gz  FASTQ   DNA      6,522     978,965       35    150.1      151
data/merged_pairs/ERR6913252.flash.extendedFrags.fastq.gz  FASTQ   DNA      8,980   1,182,504       35    131.7      292
data/merged_pairs/ERR6913252.flash.notCombined_1.fastq.gz  FASTQ   DNA        987     144,954       35    146.9      151
data/merged_pairs/ERR6913252.flash.notCombined_2.fastq.gz  FASTQ   DNA        987     144,936       35    146.8      151
data/merged_pairs/ERR6913254.flash.extendedFrags.fastq.gz  FASTQ   DNA     47,673   5,033,825       35    105.6      292
data/merged_pairs/ERR6913254.flash.notCombined_1.fastq.gz  FASTQ   DNA      2,277     238,041       35    104.5      151
data/merged_pairs/ERR6913254.flash.notCombined_2.fastq.gz  FASTQ   DNA      2,277     237,989       35    104.5      151
data/merged_pairs/ERR6913264.flash.extendedFrags.fastq.gz  FASTQ   DNA      9,930   1,186,470       35    119.5      292
data/merged_pairs/ERR6913264.flash.notCombined_1.fastq.gz  FASTQ   DNA        761      83,623       35    109.9      151
data/merged_pairs/ERR6913264.flash.notCombined_2.fastq.gz  FASTQ   DNA        761      83,740       35      110      151
data/merged_pairs/ERR6913265.flash.extendedFrags.fastq.gz  FASTQ   DNA     16,592   1,679,747       35    101.2      292
data/merged_pairs/ERR6913265.flash.notCombined_1.fastq.gz  FASTQ   DNA        855      81,853       35     95.7      151
data/merged_pairs/ERR6913265.flash.notCombined_2.fastq.gz  FASTQ   DNA        855      81,840       35     95.7      151

seqkit fq2fa data/merged_pairs/ERR6913158.flash.extendedFrags.fastq.gz > data/merged_pairs/ERR6913156.flash.extendedFrags.fna

seqkit range --range 1:101 data/merged_pairs/ERR6913156.flash.extendedFrags.fna > data/merged_pairs/ERR6913156.flash.extendedFrags.100.fna
seqkit range --range 101:1101 data/merged_pairs/ERR6913156.flash.extendedFrags.fna > data/merged_pairs/ERR6913156.flash.extendedFrags.1000.fna
seqkit range --range 1101:11101 data/merged_pairs/ERR6913156.flash.extendedFrags.fna > data/merged_pairs/ERR6913156.flash.extendedFrags.10000.fna

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

cat ./analyses/huiyu_run_accession.txt

ERR6913156
ERR6913158
ERR6913169
ERR6913264
ERR6913265
ERR6913168
ERR6913252
ERR6913254

seqkit stats data/merged_pairs/ERR6913156.*.fna

file                                                        format  type  num_seqs     sum_len  min_len  avg_len  max_len
data/merged_pairs/ERR6913156.flash.extendedFrags.10000.fna  FASTA   DNA     10,001   1,446,399       36    144.6      292
data/merged_pairs/ERR6913156.flash.extendedFrags.1000.fna   FASTA   DNA      1,001     146,176       40      146      291
data/merged_pairs/ERR6913156.flash.extendedFrags.100.fna    FASTA   DNA        101      14,125       62    139.9      285
data/merged_pairs/ERR6913156.flash.extendedFrags.fna        FASTA   DNA    690,579  99,890,771       35    144.6      292

cp scripts/generic_sbatch_array.sh scripts/fastq_subsamples_blastn_vs_viral_refseq_sbatch.sh

make dir for output before the sbatch

mkdir analyses/blastn/output

squeue -u huiyu

             JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
          33578763      fast  jupyter    huiyu  R    1:26:03      1 cpu-node-3

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

sbatch job arrays

sbatch scripts/fastq_subsamples_blastn_vs_viral_refseq_sbatch.sh

Submitted batch job 33580193

sacct -j 33580193

       JobID    JobName  Partition    Account  AllocCPUS      State ExitCode 
------------ ---------- ---------- ---------- ---------- ---------- -------- 
33580193     MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33580193.ba+      batch            2314_medb+          1  COMPLETED      0:0 
33580193.0    bastn_100            2314_medb+          1  COMPLETED      0:0 
33580193.1   bastn_1000            2314_medb+          1  COMPLETED      0:0 
33580193.2   bastn_100+            2314_medb+          1  COMPLETED      0:0 

sbatch scripts/fastq_subsamples_blastn_vs_viral_refseq_sbatch.sh

Submitted batch job 33580520

sacct -j 33580520

       JobID    JobName  Partition    Account  AllocCPUS      State ExitCode 
------------ ---------- ---------- ---------- ---------- ---------- -------- 
33580520     MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33580520.ba+      batch            2314_medb+          1  COMPLETED      0:0 
33580520.0    bastn_100            2314_medb+          1  COMPLETED      0:0 
33580520.1   bastn_1000            2314_medb+          1  COMPLETED      0:0 
33580520.2   bastn_100+            2314_medb+          1  COMPLETED      0:0 

cat analyses/blastn/fastq_subsample_blastn_vs_refseq_viral_100.tsv

grep -B 4 -A20 "significant alignments" analyses/blastn/fastq_subsample_blastn_vs_refseq_viral_10000.blast

Query= ERR6913158.917.1 917 length=94

Length=94
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_054146.1 Ralstonia phage phiRSP, complete genome                   63.9    2e-09


>NC_054146.1 Ralstonia phage phiRSP, complete genome
Length=44526

 Score = 63.9 bits (34),  Expect = 2e-09
 Identities = 34/34 (100%), Gaps = 0/34 (0%)
 Strand=Plus/Minus

Query  32     CCACCAGCGCCCGCGAAAAGAGCCAGCTCATTCA  65
              ||||||||||||||||||||||||||||||||||
Sbjct  13689  CCACCAGCGCCCGCGAAAAGAGCCAGCTCATTCA  13656



Lambda      K        H
    1.33    0.621     1.12 

--
Query= ERR6913158.1572.1 1572 length=119

Length=119
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_031904.1 Flavobacterium phage Fpv3, complete genome                215     7e-55
NC_031912.1 Flavobacterium phage Fpv20, complete genome               215     7e-55
NC_031931.1 Flavobacterium phage Fpv2, complete genome                215     7e-55
NC_031914.1 Flavobacterium phage Fpv1, complete genome                215     7e-55
NC_041872.1 Flavobacterium phage FpV4, complete genome                215     7e-55


>NC_031904.1 Flavobacterium phage Fpv3, complete genome
Length=88421

 Score = 215 bits (116),  Expect = 7e-55
 Identities = 118/119 (99%), Gaps = 0/119 (0%)
 Strand=Plus/Plus

Query  1      GGACCAAGTAATTCAAAATTAAATACCATTATTTCTCTCAATAACATTAATAATTTTGTA  60
              ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Sbjct  75200  GGACCAAGTAATTCAAAATTAAATACCATTATTTCTCTCAATAACATTAATAATTTTGTA  75259

Query  61     AACTTCTGCTATATAGTAAGGATAATAAATAATTTCCTTTATTTCTTCATCTGTTATCA  119
--
Query= ERR6913158.1708.1 1708 length=151

Length=217
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_011589.1 Stenotrophomonas phage S1, complete genome                95.3    2e-18


>NC_011589.1 Stenotrophomonas phage S1, complete genome
Length=40287

 Score = 95.3 bits (51),  Expect = 2e-18
 Identities = 118/151 (78%), Gaps = 1/151 (1%)
 Strand=Plus/Plus

Query  61    CGCGGCTACCACATCAACTGCCTGTACTACCAGTTTGGCCTGGGCCCCCGCTGGCTAGAC  120
             |||||||||  ||||||||||||||||||||||||||||||||| || |||||||| |||
Sbjct  4317  CGCGGCTACACCATCAACTGCCTGTACTACCAGTTTGGCCTGGGTCCACGCTGGCTGGAC  4376

Query  121   CTTATCGACACCTGGCGCGATGTGCAAAACGAACCCGCCCGCCTCAAAACCTTTTTAAAT  180
             ||  |  |    ||||  || | |||   ||| || ||   |||||| |||||  | || 
Sbjct  4377  CTGGTAAAAGAGTGGCTGGAGGCGCAGGGCGATCCAGCTTCCCTCAAGACCTTCGTGAAC  4436

Query  181   GACCGCCTGGCCGAGCCGTGGGAAGACGCCG  211
--
Query= ERR6913158.2013.1 2013 length=151

Length=177
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_042116.1 Yersinia phage fHe-Yen9-04 genome assembly, complete ...  137     2e-31
NC_041878.1 Pectobacterium phage CBB, complete genome                 126     5e-28
NC_019401.1 Cronobacter phage vB_CsaM_GAP32, complete genome          126     5e-28


>NC_042116.1 Yersinia phage fHe-Yen9-04 genome assembly, complete 
genome: monopartite
Length=354378

 Score = 137 bits (74),  Expect = 2e-31
 Identities = 102/116 (88%), Gaps = 0/116 (0%)
 Strand=Plus/Plus

Query  1      GTAACTCGTGATATTAACATGCGTATTAAAGCACTAGCATATGGTGTTGAAGTACAAGAT  60
              ||||||||||||||||| ||||| ||||||||||||||||||||||||||||| ||||||
Sbjct  58242  GTAACTCGTGATATTAATATGCGAATTAAAGCACTAGCATATGGTGTTGAAGTTCAAGAT  58301

Query  61     TATCGTCACGATGTAACAATCGAAGACTCAGACCTAATCCACACAGGCCACCATGC  116
              |||||||||||| ||||||| ||||| || ||  | || || ||||| || |||||
--
Query= ERR6913158.2287.1 2287 length=114

Length=114
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_048844.1 Flavobacterium phage vB_FspS_tooticki6-1, complete ge...  178     8e-44
NC_048837.1 Flavobacterium phage vB_FspS_mumin9-1, complete genome    178     8e-44
NC_048831.1 Flavobacterium phage vB_FspS_filifjonk9-1, complete g...  178     8e-44


>NC_048844.1 Flavobacterium phage vB_FspS_tooticki6-1, complete 
genome
Length=36912

 Score = 178 bits (96),  Expect = 8e-44
 Identities = 106/111 (95%), Gaps = 0/111 (0%)
 Strand=Plus/Minus

Query  4     TAACGTTATCGGGCTTGGCGAAGTGGCTGAACCCGAACTTAAATAGAATTACTAAACTTT  63
             ||||||| ||||||||||||||||||||||||| |||  |||||||||||||||||||| 
Sbjct  3728  TAACGTTTTCGGGCTTGGCGAAGTGGCTGAACCTGAAGCTAAATAGAATTACTAAACTTA  3669

Query  64    AAAATTAAAAACGAATGATTGATAGAATTACTGAACAGCCATTTTGCCAAA  114
             |||||||||||||||||||||||||||||||||||||||||||||||||||
--
Query= ERR6913158.3302.1 3302 length=139

Length=139
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_048844.1 Flavobacterium phage vB_FspS_tooticki6-1, complete ge...  185     6e-46
NC_048837.1 Flavobacterium phage vB_FspS_mumin9-1, complete genome    182     8e-45
NC_048831.1 Flavobacterium phage vB_FspS_filifjonk9-1, complete g...  182     8e-45


>NC_048844.1 Flavobacterium phage vB_FspS_tooticki6-1, complete 
genome
Length=36912

 Score = 185 bits (100),  Expect = 6e-46
 Identities = 123/134 (92%), Gaps = 1/134 (1%)
 Strand=Plus/Plus

Query  6     ACCTTCGCCAAGCCCGAAAACGTTAGTGGCAATACTCCGAAGCCCTCCGAACAGCGACAT  65
             ||| |||| |||||  |||||||||||||||||||||| ||||||| ||||| |||||||
Sbjct  2842  ACC-TCGCAAAGCCGCAAAACGTTAGTGGCAATACTCCAAAGCCCTACGAACTGCGACAT  2900

Query  66    CGTAATATTGTTTTTCCTTTTCAATACCAATTGATTTGCGATTTAATTTAATGCAAGCAA  125
             ||||||||||||||||||||||||||||||||||||| |||||||||||||||||||| |
--
Query= ERR6913158.3387.1 3387 length=106

Length=106
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_048832.1 Flavobacterium phage vB_FspS_hattifnatt9-1, complete ...  161     8e-39


>NC_048832.1 Flavobacterium phage vB_FspS_hattifnatt9-1, complete 
genome
Length=39262

 Score = 161 bits (87),  Expect = 8e-39
 Identities = 93/96 (97%), Gaps = 0/96 (0%)
 Strand=Plus/Plus

Query  11    TTCTATTTAAGTTTGTGAGAAGCCCTACCTATAACAGCACATAGGCAATATGGCGGGTTC  70
             |||| ||||| |||||||||||||||||||||||||||||||||||||||||||||||||
Sbjct  3010  TTCTGTTTAAATTTGTGAGAAGCCCTACCTATAACAGCACATAGGCAATATGGCGGGTTC  3069

Query  71    TCGGTTAATATTAAGTTCAGTTTTTCAAATCAAGTT  106
             ||||||||||||||||||||||||| ||||||||||
Sbjct  3070  TCGGTTAATATTAAGTTCAGTTTTTTAAATCAAGTT  3105

--
Query= ERR6913158.4294.1 4294 length=77

Length=77
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_054651.1 Escherichia phage C1, complete genome                     67.6    1e-10


>NC_054651.1 Escherichia phage C1, complete genome
Length=46667

 Score = 67.6 bits (36),  Expect = 1e-10
 Identities = 44/48 (92%), Gaps = 0/48 (0%)
 Strand=Plus/Minus

Query  22     AACGCTGTCCCACTTATTCTGTGTCGTCCCATACGGCAAATCGCACAA  69
              |||||| |||||||| ||  ||||||||||||||||||||||||||||
Sbjct  16880  AACGCTATCCCACTTGTTGCGTGTCGTCCCATACGGCAAATCGCACAA  16833



Lambda      K        H
    1.33    0.621     1.12 

--
Query= ERR6913158.5690.1 5690 length=149

Length=279
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_055868.1 CrAssphage cr50_1, complete genome                        54.7    4e-06


>NC_055868.1 CrAssphage cr50_1, complete genome
Length=98826

 Score = 54.7 bits (29),  Expect = 4e-06
 Identities = 29/29 (100%), Gaps = 0/29 (0%)
 Strand=Plus/Plus

Query  67     GTTCAACGACTATCCCGAAAGGGAGTACA  95
              |||||||||||||||||||||||||||||
Sbjct  55541  GTTCAACGACTATCCCGAAAGGGAGTACA  55569



Lambda      K        H
    1.33    0.621     1.12 

--
Query= ERR6913158.6257.1 6257 length=106

Length=106
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_005260.1 Aeromonas phage Aeh1, complete genome                     73.1    4e-12
NC_014636.1 Aeromonas phage phiAS5, complete genome                   71.3    1e-11


>NC_005260.1 Aeromonas phage Aeh1, complete genome
Length=233234

 Score = 73.1 bits (39),  Expect = 4e-12
 Identities = 53/60 (88%), Gaps = 0/60 (0%)
 Strand=Plus/Plus

Query  30     GTGTCTCGATCGCACTTCTGCAACAGACCACCACCCATACCGAACGCGATGTTGTCAACA  89
              ||||| || ||||| ||||||||||||||||||||||||||||| || | ||| ||||||
Sbjct  79845  GTGTCACGGTCGCATTTCTGCAACAGACCACCACCCATACCGAAAGCTACGTTTTCAACA  79904


>NC_014636.1 Aeromonas phage phiAS5, complete genome
Length=225268

--
Query= ERR6913158.6351.1 6351 length=106

Length=106
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_005260.1 Aeromonas phage Aeh1, complete genome                     73.1    4e-12
NC_014636.1 Aeromonas phage phiAS5, complete genome                   71.3    1e-11


>NC_005260.1 Aeromonas phage Aeh1, complete genome
Length=233234

 Score = 73.1 bits (39),  Expect = 4e-12
 Identities = 53/60 (88%), Gaps = 0/60 (0%)
 Strand=Plus/Plus

Query  30     GTGTCTCGATCGCACTTCTGCAACAGACCACCACCCATACCGAACGCGATGTTGTCAACA  89
              ||||| || ||||| ||||||||||||||||||||||||||||| || | ||| ||||||
Sbjct  79845  GTGTCACGGTCGCATTTCTGCAACAGACCACCACCCATACCGAAAGCTACGTTTTCAACA  79904


>NC_014636.1 Aeromonas phage phiAS5, complete genome
Length=225268

--
Query= ERR6913158.6994.1 6994 length=150

Length=217
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_055783.1 Escherichia phage vB_EcoM_005, complete genome            54.7    3e-06


>NC_055783.1 Escherichia phage vB_EcoM_005, complete genome
Length=155101

 Score = 54.7 bits (29),  Expect = 3e-06
 Identities = 31/32 (97%), Gaps = 0/32 (0%)
 Strand=Plus/Minus

Query  149    ACACCCGCATGATTTTGTTTTTCCTGTTTTTA  180
              ||| ||||||||||||||||||||||||||||
Sbjct  75994  ACAGCCGCATGATTTTGTTTTTCCTGTTTTTA  75963



Lambda      K        H
    1.33    0.621     1.12 

--
Query= ERR6913158.8370.1 8370 length=141

Length=141
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_029021.1 Enterobacteria phage JenK1, complete genome               54.7    2e-06


>NC_029021.1 Enterobacteria phage JenK1, complete genome
Length=60747

 Score = 54.7 bits (29),  Expect = 2e-06
 Identities = 35/38 (92%), Gaps = 0/38 (0%)
 Strand=Plus/Minus

Query  7      ATCACCCCAACGAATATTTCCAGGATTGCAATTACGGA  44
              ||||||||||||||||||||||||||||  ||| ||||
Sbjct  59682  ATCACCCCAACGAATATTTCCAGGATTGTTATTCCGGA  59645



Lambda      K        H
    1.33    0.621     1.12 

--
Query= ERR6913158.8734.1 8734 length=93

Length=93
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_031129.1 Salmonella phage SJ46, complete genome                    100     1e-20


>NC_031129.1 Salmonella phage SJ46, complete genome
Length=103445

 Score = 100 bits (54),  Expect = 1e-20
 Identities = 76/87 (87%), Gaps = 0/87 (0%)
 Strand=Plus/Minus

Query  7      GTGTTCTTCAACCGGCTGGGCTAAATCCGCGACAGCAGCTTTGAGCAGCAGCGCTACCGG  66
              |||||||||||||| || ||  ||||| | ||  | ||||| ||||||||||||||||||
Sbjct  58806  GTGTTCTTCAACCGCCTTGGGGAAATCAGGGATCGGAGCTTCGAGCAGCAGCGCTACCGG  58747

Query  67     GCCAGCGGCCTCAATCTGGTGACGGCG  93
              |||||||||||||| ||||||||||||
Sbjct  58746  GCCAGCGGCCTCAACCTGGTGACGGCG  58720


--
Query= ERR6913158.11319.1 11319 length=150

Length=209
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_049451.1 Klebsiella phage ST147-VIM1phi7.1, complete genome        220     3e-56
NC_049453.1 Klebsiella phage ST13-OXA48phi12.1, complete genome       215     1e-54


>NC_049451.1 Klebsiella phage ST147-VIM1phi7.1, complete genome
Length=34141

 Score = 220 bits (119),  Expect = 3e-56
 Identities = 165/188 (88%), Gaps = 0/188 (0%)
 Strand=Plus/Plus

Query  13     TCGGCCAGCTCTTCCGGGGTCGGCTCGCGGCCGATCTCGTGCAGCATCTGGCGGCTGGTG  72
              || |||||||||||||||||||| || ||||| ||||| ||||||||||| |||  | | 
Sbjct  29146  TCAGCCAGCTCTTCCGGGGTCGGTTCACGGCCCATCTCCTGCAGCATCTGACGGGAGATA  29205

Query  73     CGGACGATCTTGTTGATCGTCTCGATCATGTGCACCGGGATGCGGATGGTGCGCGCCTGG  132
              |||  || ||||||||| ||||| ||||| |||||||| || ||||||||||||||||| 
Sbjct  29206  CGGTTGAGCTTGTTGATAGTCTCAATCATATGCACCGGAATACGGATGGTGCGCGCCTGA  29265

--
Query= ERR6913158.11581.1 11581 length=150

Length=246
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_041917.1 Serratia phage BF, complete genome                        150     4e-35
NC_019401.1 Cronobacter phage vB_CsaM_GAP32, complete genome          139     1e-31


>NC_041917.1 Serratia phage BF, complete genome
Length=357154

 Score = 150 bits (81),  Expect = 4e-35
 Identities = 159/197 (81%), Gaps = 4/197 (2%)
 Strand=Plus/Plus

Query  38      CTAAAGCGGCAGGTGCTTGGGTACAAGATCCAGTTCTAGGGCTAGTGGATTACCTTGGAT  97
               ||||||| |||||||| ||||| ||||||||||| || ||  || | || | | | || |
Sbjct  189472  CTAAAGCAGCAGGTGCATGGGTTCAAGATCCAGTACTTGGTTTAATCGACTTCTTAGGCT  189531

Query  98      GTACTGACTTCAACTCCCTATACCCAACTGTACTACGTGCATTAGGTATGAGTACTGAAT  157
               ||   ||||||||||| ||||| ||||| || ||||||||||||||||||||||||||||
Sbjct  189532  GTGTAGACTTCAACTCACTATATCCAACAGTTCTACGTGCATTAGGTATGAGTACTGAAT  189591

--
Query= ERR6913158.11703.1 11703 length=151

Length=207
                                                                      Score     E
Sequences producing significant alignments:                          (Bits)  Value

NC_015265.1 Burkholderia phage KS5, complete genome                   339     7e-92


>NC_015265.1 Burkholderia phage KS5, complete genome
Length=37236

 Score = 339 bits (183),  Expect = 7e-92
 Identities = 199/207 (96%), Gaps = 0/207 (0%)
 Strand=Plus/Plus

Query  1      CGACGTTATTTAACCAGCCGGTGCCGGTATTAAAGCAGGCTTTCGCGGGAAGCGATATTC  60
              |||||||||||||||||| || ||| ||||||||||||||||||||| ||||||||||||
Sbjct  25146  CGACGTTATTTAACCAGCAGGCGCCAGTATTAAAGCAGGCTTTCGCGAGAAGCGATATTC  25205

Query  61     CGTCCGAGTTATGTCCCATGTCCGCCTAACCTAGAACGAGGGAATGTCTGGACGTAGTTT  120
              |||||||||||||||||||||||||||||||| ||||||||||||| |||||||| ||||
Sbjct  25206  CGTCCGAGTTATGTCCCATGTCCGCCTAACCTGGAACGAGGGAATGGCTGGACGTGGTTT  25265

Query  121    TGGCTATTGCGATAAAGATTCGAGGACGATTTCCGCGATCCGATCGACATCGACATCGGC  180

cp scripts/fastq_subsamples_blastn_vs_viral_refseq_sbatch.sh scripts/fastq_full_blastn_vs_viral_refseq_sbatch.sh

ls data/merged_pairs/

ERR6913156.flash.extendedFrags.10000.fna
ERR6913156.flash.extendedFrags.1000.fna
ERR6913156.flash.extendedFrags.100.fna
ERR6913156.flash.extendedFrags.fastq.gz
ERR6913156.flash.extendedFrags.fna
ERR6913156.flash.hist
ERR6913156.flash.histogram
ERR6913156.flash.notCombined_1.fastq.gz
ERR6913156.flash.notCombined_2.fastq.gz
ERR6913158.flash.extendedFrags.fastq.gz
ERR6913158.flash.hist
ERR6913158.flash.histogram
ERR6913158.flash.notCombined_1.fastq.gz
ERR6913158.flash.notCombined_2.fastq.gz
ERR6913168.flash.extendedFrags.fastq.gz
ERR6913168.flash.hist
ERR6913168.flash.histogram
ERR6913168.flash.notCombined_1.fastq.gz
ERR6913168.flash.notCombined_2.fastq.gz
ERR6913169.flash.extendedFrags.fastq.gz
ERR6913169.flash.hist
ERR6913169.flash.histogram
ERR6913169.flash.notCombined_1.fastq.gz
ERR6913169.flash.notCombined_2.fastq.gz
ERR6913252.flash.extendedFrags.fastq.gz
ERR6913252.flash.hist
ERR6913252.flash.histogram
ERR6913252.flash.notCombined_1.fastq.gz
ERR6913252.flash.notCombined_2.fastq.gz
ERR6913254.flash.extendedFrags.fastq.gz
ERR6913254.flash.hist
ERR6913254.flash.histogram
ERR6913254.flash.notCombined_1.fastq.gz
ERR6913254.flash.notCombined_2.fastq.gz
ERR6913264.flash.extendedFrags.fastq.gz
ERR6913264.flash.hist
ERR6913264.flash.histogram
ERR6913264.flash.notCombined_1.fastq.gz
ERR6913264.flash.notCombined_2.fastq.gz
ERR6913265.flash.extendedFrags.fastq.gz
ERR6913265.flash.hist
ERR6913265.flash.histogram
ERR6913265.flash.notCombined_1.fastq.gz
ERR6913265.flash.notCombined_2.fastq.gz

seqkit stats data/merged_pairs/*.fasta

file                                                    format  type  num_seqs     sum_len  min_len  avg_len  max_len
data/merged_pairs/ERR6913156.flash.extendedFrags.fasta  FASTA   DNA     22,291   3,262,339       35    146.4      292
data/merged_pairs/ERR6913158.flash.extendedFrags.fasta  FASTA   DNA    690,579  99,890,771       35    144.6      292
data/merged_pairs/ERR6913168.flash.extendedFrags.fasta  FASTA   DNA     63,620   9,531,276       35    149.8      292
data/merged_pairs/ERR6913169.flash.extendedFrags.fasta  FASTA   DNA     76,719  11,359,696       35    148.1      292
data/merged_pairs/ERR6913252.flash.extendedFrags.fasta  FASTA   DNA      8,980   1,182,504       35    131.7      292
data/merged_pairs/ERR6913254.flash.extendedFrags.fasta  FASTA   DNA     47,673   5,033,825       35    105.6      292
data/merged_pairs/ERR6913264.flash.extendedFrags.fasta  FASTA   DNA      9,930   1,186,470       35    119.5      292
data/merged_pairs/ERR6913265.flash.extendedFrags.fasta  FASTA   DNA     16,592   1,679,747       35    101.2      292

BLASTn of full FASTQ versus refseq viral database

sbatch scripts/fastq_full_blastn_vs_viral_refseq_sbatch.sh

Submitted batch job 33582512

sacct -j 33582512

       JobID    JobName  Partition    Account  AllocCPUS      State ExitCode 
------------ ---------- ---------- ---------- ---------- ---------- -------- 
33582512_1   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_1.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_1.0 ERR6913156            2314_medb+          1  COMPLETED      0:0 
33582512_2   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_2.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_2.0 ERR6913158            2314_medb+          1  COMPLETED      0:0 
33582512_3   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_3.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_3.0 ERR6913169            2314_medb+          1  COMPLETED      0:0 
33582512_4   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_4.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_4.0 ERR6913264            2314_medb+          1  COMPLETED      0:0 
33582512_5   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_5.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_5.0 ERR6913265            2314_medb+          1  COMPLETED      0:0 
33582512_6   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_6.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_6.0 ERR6913168            2314_medb+          1  COMPLETED      0:0 
33582512_7   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_7.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_7.0 ERR6913252            2314_medb+          1  COMPLETED      0:0 
33582512_8   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33582512_8.+      batch            2314_medb+          1  COMPLETED      0:0 
33582512_8.0 ERR6913254            2314_medb+          1  COMPLETED      0:0 

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS -j 33582512

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS 
-------------------- -------- ---------- ---------- -------- ---------- ---------- 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:11            
               batch        1        2Gn  COMPLETED      0:0   00:00:11      1344K 
          ERR6913156        1        2Gn  COMPLETED      0:0   00:00:09       960K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:02:26            
               batch        1        2Gn  COMPLETED      0:0   00:02:26      7964K 
          ERR6913158        1        2Gn  COMPLETED      0:0   00:02:26    478000K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:21            
               batch        1        2Gn  COMPLETED      0:0   00:00:21      1336K 
          ERR6913169        1        2Gn  COMPLETED      0:0   00:00:19       956K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:05            
               batch        1        2Gn  COMPLETED      0:0   00:00:05      1332K 
          ERR6913264        1        2Gn  COMPLETED      0:0   00:00:05       964K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:08            
               batch        1        2Gn  COMPLETED      0:0   00:00:08      1328K 
          ERR6913265        1        2Gn  COMPLETED      0:0   00:00:06       960K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:18            
               batch        1        2Gn  COMPLETED      0:0   00:00:18      1344K 
          ERR6913168        1        2Gn  COMPLETED      0:0   00:00:17       964K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:04            
               batch        1        2Gn  COMPLETED      0:0   00:00:04      1332K 
          ERR6913252        1        2Gn  COMPLETED      0:0   00:00:03       956K 
          MedBioinfo        1        2Gn  COMPLETED      0:0   00:00:11            
               batch        1        2Gn  COMPLETED      0:0   00:00:11      1336K 
          ERR6913254        1        2Gn  COMPLETED      0:0   00:00:09       972K 

wc -l analyses/blastn/*.out

   548 analyses/blastn/ERR6913156_blastn_vs_viral.out
  2808 analyses/blastn/ERR6913158_blastn_vs_viral.out
   344 analyses/blastn/ERR6913168_blastn_vs_viral.out
   383 analyses/blastn/ERR6913169_blastn_vs_viral.out
   197 analyses/blastn/ERR6913252_blastn_vs_viral.out
   488 analyses/blastn/ERR6913254_blastn_vs_viral.out
    45 analyses/blastn/ERR6913264_blastn_vs_viral.out
   133 analyses/blastn/ERR6913265_blastn_vs_viral.out
  4946 total

using a one-liner with cut sort uniq sort piped in this order, can you give the list of the viral genomes hit by your BLASTn with the number of hits (sorted by increasing number of hits) ?

• the two most important hints here are:
• • to use the -c switch of uniq (this the main secret for to make a solution possible)
• • to use the -n switch in the second instance of sort (often a forgotten issue in sorting...) The result should look something like this (first column is the number of reads that hit, the second is the accession number of the viral genome):

cut --help

Usage: cut OPTION... [FILE]...
Print selected parts of lines from each FILE to standard output.

Mandatory arguments to long options are mandatory for short options too.
  -b, --bytes=LIST        select only these bytes
  -c, --characters=LIST   select only these characters
  -d, --delimiter=DELIM   use DELIM instead of TAB for field delimiter
  -f, --fields=LIST       select only these fields;  also print any line
                            that contains no delimiter character, unless
                            the -s option is specified
  -n                      with -b: don't split multibyte characters
      --complement        complement the set of selected bytes, characters
                            or fields
  -s, --only-delimited    do not print lines not containing delimiters
      --output-delimiter=STRING  use STRING as the output delimiter
                            the default is to use the input delimiter
      --help     display this help and exit
      --version  output version information and exit

Use one, and only one of -b, -c or -f.  Each LIST is made up of one
range, or many ranges separated by commas.  Selected input is written
in the same order that it is read, and is written exactly once.
Each range is one of:

  N     N'th byte, character or field, counted from 1
  N-    from N'th byte, character or field, to end of line
  N-M   from N'th to M'th (included) byte, character or field
  -M    from first to M'th (included) byte, character or field

With no FILE, or when FILE is -, read standard input.

GNU coreutils online help: <http://www.gnu.org/software/coreutils/>
For complete documentation, run: info coreutils 'cut invocation'

cat analyses/blastn/*.out| cut -f2 | sort | uniq -c | sort -n -r | head -n5

    149 NC_048831.1
    122 NC_019401.1
    115 NC_041917.1
    104 NC_025447.1
     98 NC_048833.1
sort: write failed: standard output: Broken pipe
sort: write error

for file in analyses/blastn/*.out 
do
   echo "$file"
   cut -f2 $file | sort | uniq -c | sort -n -r | head -n5
done

analyses/blastn/ERR6913156_blastn_vs_viral.out
     26 NC_001416.1
     22 NC_019723.1
     19 NC_049955.1
     19 NC_049952.1
     19 NC_049951.1
analyses/blastn/ERR6913158_blastn_vs_viral.out
    112 NC_048831.1
     97 NC_019401.1
     95 NC_041917.1
     91 NC_025447.1
     77 NC_027364.1
analyses/blastn/ERR6913168_blastn_vs_viral.out
     33 NC_027981.1
     33 NC_004456.1
     31 NC_019722.1
     13 NC_019401.1
     11 NC_048831.1
analyses/blastn/ERR6913169_blastn_vs_viral.out
     57 NC_027981.1
     54 NC_019722.1
     52 NC_004456.1
     16 NC_048831.1
     11 NC_048842.1
analyses/blastn/ERR6913252_blastn_vs_viral.out
     76 NC_006577.2
     10 NC_003045.1
      5 NC_006213.1
      4 NC_012936.1
      3 NC_046954.1
analyses/blastn/ERR6913254_blastn_vs_viral.out
     35 NC_001405.1
     35 AC_000008.1
     35 AC_000007.1
     32 AC_000017.1
     12 NC_008168.1
analyses/blastn/ERR6913264_blastn_vs_viral.out
      4 NC_001405.1
      4 AC_000017.1
      4 AC_000008.1
      4 AC_000007.1
      3 NC_047752.1
analyses/blastn/ERR6913265_blastn_vs_viral.out
      6 NC_045512.2
      4 NC_022089.1
      3 NC_049464.1
      3 NC_008168.1
      3 NC_001405.1

BIG question: is a BLASTn of all study reads versus nt reference DB achievable ?

cd /shared/projects/2314_medbioinfo/hui/MedBioinfo23
pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

cp scripts/fastq_full_blastn_vs_viral_refseq_sbatch.sh scripts/fastq_blastn_vs_nt_refseq_sbatch.sh

mkdir analyses/fastq_subsample_blastn_vs_NT

module load seqkit

seqkit range --range 200:210 data/merged_pairs/ERR6913158.flash.extendedFrags.fasta > data/merged_pairs/ERR6913158.flash.extendedFrags.10.fasta

sbatch scripts/fastq_blastn_vs_nt_refseq_sbatch.sh

Submitted batch job 33590753

sacct -j 33590753

       JobID    JobName  Partition    Account  AllocCPUS      State ExitCode 
------------ ---------- ---------- ---------- ---------- ---------- -------- 
33590753     MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590753.ba+      batch            2314_medb+          1  COMPLETED      0:0 
33590753.0   ERR691315+            2314_medb+          1  COMPLETED      0:0 

sacct --user huiyu

       JobID    JobName  Partition    Account  AllocCPUS      State ExitCode 
------------ ---------- ---------- ---------- ---------- ---------- -------- 
33586683        jupyter       fast 2314_medb+          1 CANCELLED+      0:0 
33586683.ba+      batch            2314_medb+          1  CANCELLED     0:15 
33586683.0   batchspaw+            2314_medb+          1  COMPLETED      0:0 
33590656_1   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_1.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_1.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_2   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_2.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_2.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_3   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_3.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_3.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_4   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_4.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_4.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_5   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_5.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_5.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_6   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_6.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_6.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_7   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_7.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_7.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590656_8   MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590656_8.+      batch            2314_medb+          1  COMPLETED      0:0 
33590656_8.0 ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590730     MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590730.ba+      batch            2314_medb+          1  COMPLETED      0:0 
33590730.0   ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590753     MedBioinfo       fast 2314_medb+          1  COMPLETED      0:0 
33590753.ba+      batch            2314_medb+          1  COMPLETED      0:0 
33590753.0   ERR691315+            2314_medb+          1  COMPLETED      0:0 
33590823        jupyter       fast 2314_medb+          1    RUNNING      0:0 
33590823.ba+      batch            2314_medb+          1    RUNNING      0:0 
33590823.0   batchspaw+            2314_medb+          1    RUNNING      0:0 

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS -j 33590753

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS 
-------------------- -------- ---------- ---------- -------- ---------- ---------- 
          MedBioinfo        1       70Gn  COMPLETED      0:0   00:11:36            
               batch        1       70Gn  COMPLETED      0:0   00:11:36      7884K 
ERR6913158_bastn_10+        1       70Gn  COMPLETED      0:0   00:11:35  19648676K 

Benchmarking to estimate cpu.hours

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

#select the 
sacct -P --format=JobID%15,JobName%18,ReqCPUS,ReqMem,Timelimit,State,ExitCode,Start,elapsedRAW,CPUTimeRAW,MaxRSS,NodeList -S 2023-05-29 -j 33582512\
    | grep ERR > blastn_full_FASTQ_vs_viral_sbatch_array.sacct
cat blastn_full_FASTQ_vs_viral_sbatch_array.sacct

33582512_1.0|ERR6913156|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:17|9|9|960K|cpu-node-88
33582512_2.0|ERR6913158|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:15|146|146|478000K|cpu-node-88
33582512_3.0|ERR6913169|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:17|19|19|956K|cpu-node-88
33582512_4.0|ERR6913264|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:15|5|5|964K|cpu-node-88
33582512_5.0|ERR6913265|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:17|6|6|960K|cpu-node-88
33582512_6.0|ERR6913168|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:16|17|17|964K|cpu-node-88
33582512_7.0|ERR6913252|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:16|3|3|956K|cpu-node-88
33582512_8.0|ERR6913254|1|2Gn||COMPLETED|0:0|2023-05-29T14:56:17|9|9|972K|cpu-node-88

sqlite3 -batch -separator "|" /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
    ".import ./blastn_full_FASTQ_vs_viral_sbatch_array.sacct blastn_viral_resources_used"

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db "select * from blastn_viral_resources_used where JobID like '33582512%';"

┌──────────────┬────────────┬─────────┬────────┬───────────┬───────────┬──────────┬─────────────────────┬────────────┬────────────┬─────────┬─────────────┐
│    JobID     │  JobName   │ ReqCPUS │ ReqMem │ Timelimit │   State   │ ExitCode │        Start        │ ElapsedRAW │ CPUTimeRAW │ MaxRSS  │  NodeList   │
├──────────────┼────────────┼─────────┼────────┼───────────┼───────────┼──────────┼─────────────────────┼────────────┼────────────┼─────────┼─────────────┤
│ 33582512_1.0 │ ERR6913156 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 9          │ 9          │ 960K    │ cpu-node-88 │
│ 33582512_2.0 │ ERR6913158 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:15 │ 146        │ 146        │ 478000K │ cpu-node-88 │
│ 33582512_3.0 │ ERR6913169 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 19         │ 19         │ 956K    │ cpu-node-88 │
│ 33582512_4.0 │ ERR6913264 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:15 │ 5          │ 5          │ 964K    │ cpu-node-88 │
│ 33582512_5.0 │ ERR6913265 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 6          │ 6          │ 960K    │ cpu-node-88 │
│ 33582512_6.0 │ ERR6913168 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:16 │ 17         │ 17         │ 964K    │ cpu-node-88 │
│ 33582512_7.0 │ ERR6913252 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:16 │ 3          │ 3          │ 956K    │ cpu-node-88 │
│ 33582512_8.0 │ ERR6913254 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 9          │ 9          │ 972K    │ cpu-node-88 │
└──────────────┴────────────┴─────────┴────────┴───────────┴───────────┴──────────┴─────────────────────┴────────────┴────────────┴─────────┴─────────────┘

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db "select * from blastn_viral_resources_used;"

┌───────────────┬──────────────┬─────────┬────────┬───────────┬───────────┬──────────┬─────────────────────┬────────────┬────────────┬─────────┬─────────────┐
│     JobID     │   JobName    │ ReqCPUS │ ReqMem │ Timelimit │   State   │ ExitCode │        Start        │ ElapsedRAW │ CPUTimeRAW │ MaxRSS  │  NodeList   │
├───────────────┼──────────────┼─────────┼────────┼───────────┼───────────┼──────────┼─────────────────────┼────────────┼────────────┼─────────┼─────────────┤
│ 33575030_1.1  │ ERR6913174   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:03:56 │ 20         │ 480        │ 1252K   │ cpu-node-15 │
│ 33575030_2.1  │ ERR6913270   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:09 │ 19         │ 456        │ 1232K   │ cpu-node-27 │
│ 33575030_3.1  │ ERR6913175   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:17 │ 30         │ 720        │ 236340K │ cpu-node-29 │
│ 33575030_4.1  │ ERR6913271   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:18 │ 109        │ 2616       │ 578788K │ cpu-node-33 │
│ 33575030_5.1  │ ERR6913176   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:18 │ 89         │ 2136       │ 764940K │ cpu-node-40 │
│ 33575030_6.1  │ ERR6913272   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:16 │ 10         │ 240        │ 1240K   │ cpu-node-43 │
│ 33575030_7.1  │ ERR6913177   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:20 │ 120        │ 2880       │ 593872K │ cpu-node-67 │
│ 33575030_8.1  │ ERR6913273   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:18 │ 3          │ 72         │ 1152K   │ cpu-node-88 │
│ 33575030_9.1  │ ERR6913178   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:19 │ 62         │ 1488       │ 567752K │ cpu-node-1  │
│ 33575030_10.1 │ ERR6913274   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-28T12:04:17 │ 5          │ 120        │ 1244K   │ cpu-node-1  │
│ 33583170_2.1  │ ERR6913141   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:03 │ 278        │ 278        │ 459676K │ cpu-node-88 │
│ 33583170_3.1  │ ERR6913142   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:57 │ 129        │ 129        │ 443964K │ cpu-node-88 │
│ 33583170_4.1  │ ERR6913143   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:58 │ 166        │ 166        │ 438488K │ cpu-node-88 │
│ 33583170_5.1  │ ERR6913144   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:01 │ 236        │ 236        │ 438768K │ cpu-node-88 │
│ 33583170_6.1  │ ERR6913240   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:05 │ 224        │ 224        │ 461388K │ cpu-node-88 │
│ 33583170_7.1  │ ERR6913201   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:50 │ 27         │ 27         │ 960K    │ cpu-node-88 │
│ 33583170_8.1  │ ERR6913237   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:07 │ 302        │ 302        │ 467960K │ cpu-node-88 │
│ 33583170_9.1  │ ERR6913238   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:10 │ 341        │ 341        │ 460300K │ cpu-node-88 │
│ 33583170_10.1 │ ERR6913239   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:22:07 │ 338        │ 338        │ 465116K │ cpu-node-88 │
│ 33581928_1.1  │ ERR6913298   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 952K    │ cpu-node-88 │
│ 33581928_2.1  │ ERR6913299   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 956K    │ cpu-node-88 │
│ 33581928_3.1  │ ERR6913222   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 964K    │ cpu-node-88 │
│ 33581928_4.1  │ ERR6913295   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 964K    │ cpu-node-88 │
│ 33581928_5.1  │ ERR6913126   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 960K    │ cpu-node-88 │
│ 33581928_6.1  │ ERR6913324   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 960K    │ cpu-node-88 │
│ 33581928_7.1  │ ERR6913327   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 964K    │ cpu-node-88 │
│ 33581928_8.1  │ ERR6913328   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:37:15 │ 1          │ 1          │ 964K    │ cpu-node-88 │
│ 33581582_1.1  │ ERR6913183   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:44 │ 1          │ 1          │ 1048K   │ cpu-node-33 │
│ 33581582_2.1  │ ERR6913279   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:37 │ 0          │ 0          │ 1028K   │ cpu-node-67 │
│ 33581582_3.1  │ ERR6913184   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:37 │ 0          │ 0          │ 1216K   │ cpu-node-67 │
│ 33581582_4.1  │ ERR6913280   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:37 │ 1          │ 1          │ 1048K   │ cpu-node-67 │
│ 33581582_5.1  │ ERR6913185   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:36 │ 0          │ 0          │ 1048K   │ cpu-node-67 │
│ 33581582_6.1  │ ERR6913281   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:37 │ 0          │ 0          │ 1224K   │ cpu-node-67 │
│ 33581582_7.1  │ ERR6913186   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:37 │ 0          │ 0          │ 1224K   │ cpu-node-67 │
│ 33581582_8.1  │ ERR6913282   │ 1       │ 4Gn    │           │ FAILED    │ 1:0      │ 2023-05-29T14:28:35 │ 1          │ 1          │ 1052K   │ cpu-node-67 │
│ 33583140_1.1  │ ERR6913174_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:20 │ 20         │ 20         │ 968K    │ cpu-node-88 │
│ 33583140_2.1  │ ERR6913177_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:35 │ 280        │ 280        │ 539936K │ cpu-node-88 │
│ 33583140_3.1  │ ERR6913272_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:20 │ 18         │ 18         │ 952K    │ cpu-node-88 │
│ 33583140_4.1  │ ERR6913174_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:21 │ 30         │ 30         │ 142920K │ cpu-node-88 │
│ 33583140_5.1  │ ERR6913178_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:25 │ 109        │ 109        │ 446800K │ cpu-node-88 │
│ 33583140_6.1  │ ERR6913272_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:20 │ 18         │ 18         │ 964K    │ cpu-node-88 │
│ 33583140_7.1  │ ERR6913175_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:22 │ 54         │ 54         │ 555992K │ cpu-node-88 │
│ 33583140_8.1  │ ERR6913178_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:26 │ 148        │ 148        │ 551640K │ cpu-node-88 │
│ 33583140_9.1  │ ERR6913273_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:19 │ 4          │ 4          │ 960K    │ cpu-node-88 │
│ 33583140_10.1 │ ERR6913175_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:22 │ 56         │ 56         │ 259892K │ cpu-node-88 │
│ 33583140_11.1 │ ERR6913270_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:21 │ 44         │ 44         │ 370220K │ cpu-node-88 │
│ 33583140_12.1 │ ERR6913273_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:19 │ 6          │ 6          │ 948K    │ cpu-node-88 │
│ 33583140_13.1 │ ERR6913176_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:28 │ 201        │ 201        │ 549720K │ cpu-node-88 │
│ 33583140_14.1 │ ERR6913270_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:20 │ 30         │ 30         │ 143956K │ cpu-node-88 │
│ 33583140_15.1 │ ERR6913274_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:18 │ 9          │ 9          │ 956K    │ cpu-node-88 │
│ 33583140_16.1 │ ERR6913176_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:30 │ 209        │ 209        │ 550120K │ cpu-node-88 │
│ 33583140_17.1 │ ERR6913271_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:29 │ 193        │ 193        │ 531104K │ cpu-node-88 │
│ 33583140_18.1 │ ERR6913274_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:18 │ 9          │ 9          │ 964K    │ cpu-node-88 │
│ 33583140_19.1 │ ERR6913177_1 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:32 │ 197        │ 197        │ 538448K │ cpu-node-88 │
│ 33583140_20.1 │ ERR6913271_2 │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:21:25 │ 182        │ 182        │ 531744K │ cpu-node-88 │
│ 33582344_1.1  │ ERR6913341   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:37 │ 466        │ 5592       │ 443556K │ cpu-node-64 │
│ 33582344_2.1  │ ERR6913345   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:20 │ 169        │ 2028       │ 568284K │ cpu-node-88 │
│ 33582344_3.1  │ ERR6913314   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:20 │ 131        │ 1572       │ 379576K │ cpu-node-33 │
│ 33582344_4.1  │ ERR6913316   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:17 │ 72         │ 864        │ 376496K │ cpu-node-33 │
│ 33582344_5.1  │ ERR6913312   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:18 │ 54         │ 648        │ 567088K │ cpu-node-67 │
│ 33582344_6.1  │ ERR6913315   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:17 │ 40         │ 480        │ 359192K │ cpu-node-67 │
│ 33582344_7.1  │ ERR6913343   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:22 │ 185        │ 2220       │ 422700K │ cpu-node-1  │
│ 33582344_8.1  │ ERR6913344   │ 12      │ 10Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:50:21 │ 117        │ 1404       │ 394624K │ cpu-node-1  │
│ 33582308_1.1  │ ERR6913148   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:20 │ 48         │ 48         │ 356980K │ cpu-node-33 │
│ 33582308_2.1  │ ERR6913244   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:30 │ 244        │ 244        │ 460200K │ cpu-node-33 │
│ 33582308_3.1  │ ERR6913149   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:25 │ 143        │ 143        │ 454356K │ cpu-node-67 │
│ 33582308_4.1  │ ERR6913245   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:33 │ 1533       │ 1533       │ 466764K │ cpu-node-46 │
│ 33582308_5.1  │ ERR6913150   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:25 │ 652        │ 652        │ 458780K │ cpu-node-46 │
│ 33582308_6.1  │ ERR6913246   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:35 │ 400        │ 400        │ 459320K │ cpu-node-42 │
│ 33582308_7.1  │ ERR6913151   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:20 │ 69         │ 69         │ 437176K │ cpu-node-42 │
│ 33582308_8.1  │ ERR6913247   │ 1       │ 25Gn   │           │ COMPLETED │ 0:0      │ 2023-05-29T14:48:29 │ 220        │ 220        │ 449156K │ cpu-node-43 │
│ 33582209_1.1  │ ERR6913114   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:37 │ 30         │ 60         │ 1232K   │ cpu-node-1  │
│ 33582209_2.1  │ ERR6913123   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:38 │ 40         │ 80         │ 475980K │ cpu-node-67 │
│ 33582209_3.1  │ ERR6913124   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:37 │ 14         │ 28         │ 1220K   │ cpu-node-67 │
│ 33582209_4.1  │ ERR6913155   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:36 │ 3          │ 6          │ 1232K   │ cpu-node-67 │
│ 33582209_5.1  │ ERR6913251   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:35 │ 3          │ 6          │ 1228K   │ cpu-node-67 │
│ 33582209_6.1  │ ERR6913219   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:38 │ 54         │ 108        │ 395628K │ cpu-node-88 │
│ 33582209_7.1  │ ERR6913210   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:37 │ 12         │ 24         │ 1144K   │ cpu-node-88 │
│ 33582209_8.1  │ ERR6913220   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:45:35 │ 11         │ 22         │ 1144K   │ cpu-node-88 │
│ 33582872_1.1  │ ERR6913131   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:20 │ 95         │ 1140       │ 500132K │ cpu-node-88 │
│ 33582872_2.1  │ ERR6913132   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:22 │ 89         │ 1068       │ 465368K │ cpu-node-15 │
│ 33582872_3.1  │ ERR6913133   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:20 │ 64         │ 768        │ 506140K │ cpu-node-15 │
│ 33582872_4.1  │ ERR6913134   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:19 │ 12         │ 144        │ 1224K   │ cpu-node-33 │
│ 33582872_5.1  │ ERR6913227   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:24 │ 212        │ 2544       │ 560744K │ cpu-node-33 │
│ 33582872_6.1  │ ERR6913229   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:23 │ 143        │ 1716       │ 489888K │ cpu-node-67 │
│ 33582872_7.1  │ ERR6913104   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:18 │ 33         │ 396        │ 432180K │ cpu-node-67 │
│ 33582872_8.1  │ ERR6913200   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:22 │ 61         │ 732        │ 404852K │ cpu-node-25 │
│ 33582872_9.1  │ ERR6913230   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:19 │ 34         │ 408        │ 186176K │ cpu-node-25 │
│ 33582872_10.1 │ ERR6913228   │ 12      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:22 │ 110        │ 1320       │ 422036K │ cpu-node-25 │
│ 33582902_1.1  │ ERR6913313   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:59 │ 280        │ 280        │ 549348K │ cpu-node-33 │
│ 33582902_2.1  │ ERR6913342   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:12:11 │ 464        │ 464        │ 473524K │ cpu-node-33 │
│ 33582902_3.1  │ ERR6913294   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:12:03 │ 309        │ 309        │ 536496K │ cpu-node-33 │
│ 33582902_4.1  │ ERR6913323   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:12:07 │ 357        │ 357        │ 549492K │ cpu-node-33 │
│ 33582902_5.1  │ ERR6913161   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:50 │ 11         │ 11         │ 1044K   │ cpu-node-67 │
│ 33582902_6.1  │ ERR6913257   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:50 │ 9          │ 9          │ 1048K   │ cpu-node-67 │
│ 33582902_7.1  │ ERR6913171   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:51 │ 31         │ 31         │ 248852K │ cpu-node-67 │
│ 33582902_8.1  │ ERR6913267   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:11:48 │ 12         │ 12         │ 1044K   │ cpu-node-67 │
│ 33582668_1.1  │ ERR6913135   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:49 │ 79         │ 1896       │ 597748K │ cpu-node-15 │
│ 33582668_2.1  │ ERR6913231   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:52 │ 184        │ 4416       │ 630128K │ cpu-node-43 │
│ 33582668_3.1  │ ERR6913121   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:47 │ 10         │ 240        │ 1240K   │ cpu-node-1  │
│ 33582668_4.1  │ ERR6913217   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:46 │ 16         │ 384        │ 1248K   │ cpu-node-1  │
│ 33582668_5.1  │ ERR6913297   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:50 │ 110        │ 2640       │ 717952K │ cpu-node-25 │
│ 33582668_6.1  │ ERR6913326   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:51 │ 118        │ 2832       │ 720488K │ cpu-node-25 │
│ 33582668_7.1  │ ERR6913106   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:49 │ 68         │ 1632       │ 515412K │ cpu-node-27 │
│ 33582668_8.1  │ ERR6913202   │ 24      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:00:49 │ 81         │ 1944       │ 587080K │ cpu-node-28 │
│ 33582512_1.0  │ ERR6913156   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 9          │ 9          │ 960K    │ cpu-node-88 │
│ 33582512_2.0  │ ERR6913158   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:15 │ 146        │ 146        │ 478000K │ cpu-node-88 │
│ 33582512_3.0  │ ERR6913169   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 19         │ 19         │ 956K    │ cpu-node-88 │
│ 33582512_4.0  │ ERR6913264   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:15 │ 5          │ 5          │ 964K    │ cpu-node-88 │
│ 33582512_5.0  │ ERR6913265   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 6          │ 6          │ 960K    │ cpu-node-88 │
│ 33582512_6.0  │ ERR6913168   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:16 │ 17         │ 17         │ 964K    │ cpu-node-88 │
│ 33582512_7.0  │ ERR6913252   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:16 │ 3          │ 3          │ 956K    │ cpu-node-88 │
│ 33582512_8.0  │ ERR6913254   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:56:17 │ 9          │ 9          │ 972K    │ cpu-node-88 │
│ 33583723_1.1  │ ERR6913103   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:28 │ 40         │ 80         │ 175240K │ cpu-node-41 │
│ 33583723_2.1  │ ERR6913128   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:33 │ 101        │ 202        │ 443260K │ cpu-node-1  │
│ 33583723_3.1  │ ERR6913199   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:28 │ 7          │ 14         │ 1224K   │ cpu-node-1  │
│ 33583723_4.1  │ ERR6913224   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:36 │ 140        │ 280        │ 479524K │ cpu-node-1  │
│ 33583723_5.1  │ ERR6913115   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:29 │ 4          │ 8          │ 1228K   │ cpu-node-1  │
│ 33583723_6.1  │ ERR6913211   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:29 │ 6          │ 12         │ 1232K   │ cpu-node-1  │
│ 33583723_7.1  │ ERR6913117   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:28 │ 29         │ 58         │ 1224K   │ cpu-node-1  │
│ 33583723_8.1  │ ERR6913213   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:29 │ 5          │ 10         │ 1060K   │ cpu-node-1  │
│ 33583723_9.1  │ ERR6913111   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:28 │ 5          │ 10         │ 1220K   │ cpu-node-33 │
│ 33583723_10.1 │ ERR6913207   │ 2       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:01:28 │ 3          │ 6          │ 1224K   │ cpu-node-33 │
│ 33582427_1.1  │ ERR6913173   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:52:45 │ 3          │ 3          │ 1008K   │ cpu-node-80 │
│ 33582427_2.1  │ ERR6913137   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:52:52 │ 129        │ 129        │ 455156K │ cpu-node-12 │
│ 33582427_3.1  │ ERR6913159   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:52:45 │ 3          │ 3          │ 1064K   │ cpu-node-61 │
│ 33582427_4.1  │ ERR6913166   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:52:45 │ 12         │ 12         │ 1060K   │ cpu-node-5  │
│ 33582427_5.1  │ ERR6913255   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:52:45 │ 2          │ 2          │ 1060K   │ cpu-node-6  │
│ 33582427_6.1  │ ERR6913262   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:53:15 │ 3          │ 3          │ 1004K   │ cpu-node-80 │
│ 33582427_7.1  │ ERR6913269   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:53:15 │ 4          │ 4          │ 1056K   │ cpu-node-61 │
│ 33582427_8.1  │ ERR6913233   │ 1       │ 250Gn  │           │ COMPLETED │ 0:0      │ 2023-05-29T14:53:30 │ 253        │ 253        │ 475820K │ cpu-node-5  │
│ 33582771_2.1  │ ERR6913102   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:19 │ 0          │ 0          │ 968K    │ cpu-node-88 │
│ 33582771_3.1  │ ERR6913189   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:25 │ 124        │ 124        │ 438384K │ cpu-node-88 │
│ 33582771_4.1  │ ERR6913285   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:40 │ 219        │ 219        │ 469788K │ cpu-node-38 │
│ 33582771_5.1  │ ERR6913187   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:21 │ 30         │ 30         │ 145756K │ cpu-node-38 │
│ 33582771_6.1  │ ERR6913283   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:20 │ 29         │ 29         │ 1052K   │ cpu-node-36 │
│ 33582771_7.1  │ ERR6913284   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:30 │ 159        │ 159        │ 466296K │ cpu-node-36 │
│ 33582771_8.1  │ ERR6913188   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:05:28 │ 152        │ 152        │ 438412K │ cpu-node-37 │
│ 33581964_1.1  │ ERR6913179   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:25 │ 121        │ 121        │ 439764K │ cpu-node-1  │
│ 33581964_2.1  │ ERR6913180   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:31 │ 263        │ 263        │ 430200K │ cpu-node-1  │
│ 33581964_3.1  │ ERR6913181   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:30 │ 242        │ 242        │ 436824K │ cpu-node-1  │
│ 33581964_4.1  │ ERR6913182   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:28 │ 209        │ 209        │ 448832K │ cpu-node-1  │
│ 33581964_5.1  │ ERR6913276   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:36 │ 408        │ 408        │ 505756K │ cpu-node-33 │
│ 33581964_6.1  │ ERR6913278   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:35 │ 339        │ 339        │ 447052K │ cpu-node-33 │
│ 33581964_7.1  │ ERR6913101   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:22 │ 87         │ 87         │ 490192K │ cpu-node-33 │
│ 33581964_8.1  │ ERR6913197   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:22 │ 99         │ 99         │ 496332K │ cpu-node-33 │
│ 33581964_9.1  │ ERR6913275   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:20 │ 81         │ 81         │ 436940K │ cpu-node-33 │
│ 33581964_10.1 │ ERR6913277   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:28 │ 215        │ 215        │ 470340K │ cpu-node-67 │
│ 33584141_1.1  │ ERR6913170   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:32:59 │ 2          │ 8          │ 1240K   │ cpu-node-15 │
│ 33584141_2.1  │ ERR6913266   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:32:59 │ 2          │ 8          │ 1236K   │ cpu-node-67 │
│ 33584141_3.1  │ ERR6913109   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:32:59 │ 4          │ 16         │ 1236K   │ cpu-node-67 │
│ 33584141_4.1  │ ERR6913164   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:32:59 │ 14         │ 56         │ 1244K   │ cpu-node-67 │
│ 33584141_5.1  │ ERR6913172   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:33:01 │ 57         │ 228        │ 502896K │ cpu-node-67 │
│ 33584141_6.1  │ ERR6913260   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:32:59 │ 3          │ 12         │ 1240K   │ cpu-node-67 │
│ 33584141_7.1  │ ERR6913268   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:33:00 │ 20         │ 80         │ 1228K   │ cpu-node-67 │
│ 33584141_8.1  │ ERR6913205   │ 4       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:33:00 │ 31         │ 124        │ 374956K │ cpu-node-44 │
│ 33582171_1.1  │ ERR6913191   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:35 │ 16         │ 384        │ 1252K   │ cpu-node-15 │
│ 33582171_2.1  │ ERR6913193   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:36 │ 52         │ 1248       │ 214332K │ cpu-node-33 │
│ 33582171_3.1  │ ERR6913236   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:42 │ 220        │ 5280       │ 616116K │ cpu-node-43 │
│ 33582171_4.1  │ ERR6913291   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:41 │ 150        │ 3600       │ 569796K │ cpu-node-67 │
│ 33582171_5.1  │ ERR6913140   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:40 │ 94         │ 2256       │ 592656K │ cpu-node-1  │
│ 33582171_6.1  │ ERR6913195   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:38 │ 88         │ 2112       │ 329476K │ cpu-node-1  │
│ 33582171_7.1  │ ERR6913287   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:39 │ 125        │ 3000       │ 497960K │ cpu-node-25 │
│ 33582171_8.1  │ ERR6913289   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:44:39 │ 105        │ 2520       │ 588984K │ cpu-node-25 │
│ 33581966_1.1  │ ERR6913147   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:18 │ 83         │ 1992       │ 585232K │ cpu-node-57 │
│ 33581966_2.1  │ ERR6913154   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:15 │ 6          │ 144        │ 1240K   │ cpu-node-57 │
│ 33581966_3.1  │ ERR6913157   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:16 │ 13         │ 312        │ 1236K   │ cpu-node-27 │
│ 33581966_4.1  │ ERR6913165   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:16 │ 15         │ 360        │ 1244K   │ cpu-node-28 │
│ 33581966_5.1  │ ERR6913250   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:17 │ 11         │ 264        │ 1240K   │ cpu-node-29 │
│ 33581966_6.1  │ ERR6913243   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:21 │ 143        │ 3432       │ 687936K │ cpu-node-36 │
│ 33581966_7.1  │ ERR6913253   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:17 │ 4          │ 96         │ 1260K   │ cpu-node-37 │
│ 33581966_8.1  │ ERR6913261   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:38:17 │ 2          │ 48         │ 1260K   │ cpu-node-38 │
│ 33582026_1.1  │ ERR6913288   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:19 │ 118        │ 2832       │ 604504K │ cpu-node-15 │
│ 33582026_2.1  │ ERR6913310   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:18 │ 164        │ 3936       │ 597524K │ cpu-node-33 │
│ 33582026_3.1  │ ERR6913192   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:16 │ 36         │ 864        │ 340764K │ cpu-node-43 │
│ 33582026_4.1  │ ERR6913309   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:15 │ 26         │ 624        │ 1240K   │ cpu-node-57 │
│ 33582026_5.1  │ ERR6913311   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:17 │ 82         │ 1968       │ 681648K │ cpu-node-67 │
│ 33582026_6.1  │ ERR6913338   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:18 │ 75         │ 1800       │ 301328K │ cpu-node-1  │
│ 33582026_7.1  │ ERR6913339   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:21 │ 145        │ 3480       │ 637936K │ cpu-node-1  │
│ 33582026_8.1  │ ERR6913340   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T14:39:21 │ 131        │ 3144       │ 602788K │ cpu-node-25 │
│ 33584167_1.1  │ ERR6913120   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:30 │ 16         │ 384        │ 1240K   │ cpu-node-43 │
│ 33584167_2.1  │ ERR6913216   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:31 │ 6          │ 144        │ 1232K   │ cpu-node-67 │
│ 33584167_3.1  │ ERR6913221   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:30 │ 3          │ 72         │ 1172K   │ cpu-node-88 │
│ 33584167_4.1  │ ERR6913293   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:32 │ 46         │ 1104       │ 562276K │ cpu-node-25 │
│ 33584167_5.1  │ ERR6913125   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:31 │ 10         │ 240        │ 1264K   │ cpu-node-25 │
│ 33584167_6.1  │ ERR6913215   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:30 │ 6          │ 144        │ 1232K   │ cpu-node-27 │
│ 33584167_7.1  │ ERR6913322   │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:35 │ 154        │ 3696       │ 717448K │ cpu-node-28 │
│ 33584168_1.1  │ ERR6913139   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:43 │ 217        │ 217        │ 449212K │ cpu-node-67 │
│ 33584168_2.1  │ ERR6913235   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:46 │ 284        │ 284        │ 464224K │ cpu-node-67 │
│ 33584168_3.1  │ ERR6913145   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:35 │ 77         │ 77         │ 314788K │ cpu-node-67 │
│ 33584168_4.1  │ ERR6913241   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:46 │ 245        │ 245        │ 375932K │ cpu-node-67 │
│ 33584168_5.1  │ ERR6913146   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:33 │ 57         │ 57         │ 465084K │ cpu-node-67 │
│ 33584168_6.1  │ ERR6913242   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:50 │ 230        │ 230        │ 494844K │ cpu-node-67 │
│ 33584168_7.1  │ ERR6913107   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:31 │ 21         │ 21         │ 1044K   │ cpu-node-1  │
│ 33584168_8.1  │ ERR6913203   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T16:37:31 │ 8          │ 8          │ 1048K   │ cpu-node-1  │
│ 33583541_1.1  │ ERR6913112   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:25 │ 4          │ 48         │ 1232K   │ cpu-node-1  │
│ 33583541_2.1  │ ERR6913113   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:25 │ 19         │ 228        │ 1228K   │ cpu-node-33 │
│ 33583541_3.1  │ ERR6913320   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:27 │ 121        │ 1452       │ 443864K │ cpu-node-33 │
│ 33583541_4.1  │ ERR6913209   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:25 │ 2          │ 24         │ 1228K   │ cpu-node-43 │
│ 33583541_5.1  │ ERR6913122   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:27 │ 45         │ 540        │ 398692K │ cpu-node-43 │
│ 33583541_6.1  │ ERR6913208   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:25 │ 6          │ 72         │ 1228K   │ cpu-node-67 │
│ 33583541_7.1  │ ERR6913218   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:24 │ 16         │ 192        │ 1228K   │ cpu-node-67 │
│ 33583541_8.1  │ ERR6913349   │ 12      │ 5Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:36:29 │ 174        │ 2088       │ 565848K │ cpu-node-88 │
│ 33582966_1.2  │ ERR6913129_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:20 │ 30         │ 720        │ 1252K   │ cpu-node-15 │
│ 33582966_1.3  │ ERR6913129_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:50 │ 27         │ 648        │ 1248K   │ cpu-node-15 │
│ 33582966_2.2  │ ERR6913130_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:21 │ 45         │ 1080       │ 654200K │ cpu-node-23 │
│ 33582966_2.3  │ ERR6913130_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:15:06 │ 40         │ 960        │ 487608K │ cpu-node-23 │
│ 33582966_3.2  │ ERR6913194_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:26 │ 101        │ 2424       │ 560264K │ cpu-node-43 │
│ 33582966_3.3  │ ERR6913194_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:16:07 │ 101        │ 2424       │ 639208K │ cpu-node-43 │
│ 33582966_4.2  │ ERR6913196_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:26 │ 127        │ 3048       │ 681656K │ cpu-node-25 │
│ 33582966_4.3  │ ERR6913196_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:16:33 │ 126        │ 3024       │ 514504K │ cpu-node-25 │
│ 33582966_5.2  │ ERR6913225_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:29 │ 147        │ 3528       │ 564M    │ cpu-node-25 │
│ 33582966_5.3  │ ERR6913225_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:16:56 │ 148        │ 3552       │ 689636K │ cpu-node-25 │
│ 33582966_6.2  │ ERR6913290_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:28 │ 151        │ 3624       │ 455952K │ cpu-node-27 │
│ 33582966_6.3  │ ERR6913290_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:16:59 │ 155        │ 3720       │ 696924K │ cpu-node-27 │
│ 33582966_7.2  │ ERR6913292_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:28 │ 160        │ 3840       │ 655824K │ cpu-node-28 │
│ 33582966_7.3  │ ERR6913292_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:17:08 │ 159        │ 3816       │ 508940K │ cpu-node-28 │
│ 33582966_8.2  │ ERR6913226_1 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:14:29 │ 163        │ 3912       │ 672988K │ cpu-node-29 │
│ 33582966_8.3  │ ERR6913226_2 │ 24      │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T15:17:12 │ 161        │ 3864       │ 684616K │ cpu-node-29 │
│ 33584321_1.1  │ ERR6913116   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:32 │ 7          │ 7          │ 1064K   │ cpu-node-33 │
│ 33584321_2.1  │ ERR6913212   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:31 │ 4          │ 4          │ 1056K   │ cpu-node-33 │
│ 33584321_3.1  │ ERR6913136   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:42 │ 182        │ 182        │ 437004K │ cpu-node-33 │
│ 33584321_4.1  │ ERR6913232   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:49 │ 347        │ 347        │ 475712K │ cpu-node-33 │
│ 33584321_5.1  │ ERR6913118   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:32 │ 20         │ 20         │ 1064K   │ cpu-node-33 │
│ 33584321_6.1  │ ERR6913214   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:32 │ 12         │ 12         │ 1060K   │ cpu-node-1  │
│ 33584321_7.1  │ ERR6913108   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:32 │ 24         │ 24         │ 1060K   │ cpu-node-1  │
│ 33584321_8.1  │ ERR6913204   │ 1       │ 2Gn    │           │ COMPLETED │ 0:0      │ 2023-05-29T17:02:31 │ 7          │ 7          │ 1056K   │ cpu-node-1  │
└───────────────┴──────────────┴─────────┴────────┴───────────┴───────────┴──────────┴─────────────────────┴────────────┴────────────┴─────────┴─────────────┘

library(DBI)
mydb <- dbConnect(RSQLite::SQLite(), "/shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db")
res_used <-dbGetQuery(mydb, 'select JobName,CPUTimeRAW,MaxRSS,read_count,base_count,patient_code,host_disease_status,nuc from blastn_viral_resources_used \
cpu inner join sample_annot spl on cpu.JobName=spl.run_accession;')
head(res_used)

A data.frame: 6 × 8

	JobName	CPUTimeRAW	MaxRSS	read_count	base_count	patient_code	host_disease_status	nuc
	<chr>	<int>	<chr>	<int>	<int>	<chr>	<chr>	<chr>
1	ERR6913101	87	490192K	658268	80692720	P4	SARS-CoV-2 positive	DNA
2	ERR6913102	0	968K	102524	13193813	P11	SARS-CoV-2 positive	DNA
3	ERR6913103	80	175240K	385740	49060845	P19	SARS-CoV-2 positive	DNA
4	ERR6913104	396	432180K	610606	76430173	P22	SARS-CoV-2 positive	DNA
5	ERR6913106	1632	515412K	1271618	168661241	P55	SARS-CoV-2 positive	DNA
6	ERR6913107	21	1044K	190648	24785538	P66	SARS-CoV-2 positive	DNA

res_used$minutes <- as.integer(res_used$CPUTimeRAW) / 60
res_used$read_M  <- res_used$read_count / 1000000
res_used$ram_M   <- as.numeric(sub('K$','', res_used$MaxRSS, perl = TRUE)) / 1000
res_used$pat     <- as.factor(res_used$patient_code)
head(res_used)

A data.frame: 6 × 12

	JobName	CPUTimeRAW	MaxRSS	read_count	base_count	patient_code	host_disease_status	nuc	minutes	read_M	ram_M	pat
	<chr>	<int>	<chr>	<int>	<int>	<chr>	<chr>	<chr>	<dbl>	<dbl>	<dbl>	<fct>
1	ERR6913101	87	490192K	658268	80692720	P4	SARS-CoV-2 positive	DNA	1.450000	0.658268	490.192	P4
2	ERR6913102	0	968K	102524	13193813	P11	SARS-CoV-2 positive	DNA	0.000000	0.102524	0.968	P11
3	ERR6913103	80	175240K	385740	49060845	P19	SARS-CoV-2 positive	DNA	1.333333	0.385740	175.240	P19
4	ERR6913104	396	432180K	610606	76430173	P22	SARS-CoV-2 positive	DNA	6.600000	0.610606	432.180	P22
5	ERR6913106	1632	515412K	1271618	168661241	P55	SARS-CoV-2 positive	DNA	27.200000	1.271618	515.412	P55
6	ERR6913107	21	1044K	190648	24785538	P66	SARS-CoV-2 positive	DNA	0.350000	0.190648	1.044	P66

library(ggplot2)

ggplot(res_used, aes(x=ram_M, y=minutes)) + 
  geom_point()+
  geom_smooth(method=lm)+
  theme_bw()

`geom_smooth()` using formula 'y ~ x'

DAY2

cd /shared/projects/2314_medbioinfo/hui/MedBioinfo23
pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

mkdir analyses/kraken2

module load kraken2

kraken2 --help

Usage: kraken2 [options] <filename(s)>

Options:
  --db NAME               Name for Kraken 2 DB
                          (default: none)
  --threads NUM           Number of threads (default: 1)
  --quick                 Quick operation (use first hit or hits)
  --unclassified-out FILENAME
                          Print unclassified sequences to filename
  --classified-out FILENAME
                          Print classified sequences to filename
  --output FILENAME       Print output to filename (default: stdout); "-" will
                          suppress normal output
  --confidence FLOAT      Confidence score threshold (default: 0.0); must be
                          in [0, 1].
  --minimum-base-quality NUM
                          Minimum base quality used in classification (def: 0,
                          only effective with FASTQ input).
  --report FILENAME       Print a report with aggregrate counts/clade to file
  --use-mpa-style         With --report, format report output like Kraken 1's
                          kraken-mpa-report
  --report-zero-counts    With --report, report counts for ALL taxa, even if
                          counts are zero
  --report-minimizer-data With --report, report minimizer and distinct minimizer
                          count information in addition to normal Kraken report
  --memory-mapping        Avoids loading database into RAM
  --paired                The filenames provided have paired-end reads
  --use-names             Print scientific names instead of just taxids
  --gzip-compressed       Input files are compressed with gzip
  --bzip2-compressed      Input files are compressed with bzip2
  --minimum-hit-groups NUM
                          Minimum number of hit groups (overlapping k-mers
                          sharing the same minimizer) needed to make a call
                          (default: 2)
  --help                  Print this message
  --version               Print version information

If none of the *-compressed flags are specified, and the filename provided
is a regular file, automatic format detection is attempted.

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

cp scripts/fastq_blastn_vs_nt_refseq_sbatch.sh scripts/kraken_sbatch.sh

ls /shared/projects/2314_medbioinfo/kraken2/arch_bact_vir_hum_protoz_fung/

database100mers.kmer_distrib  database50mers.kmer_distrib  opts.k2d
database150mers.kmer_distrib  database75mers.kmer_distrib  seqid2taxid.map
database200mers.kmer_distrib  hash.k2d			   taxo.k2d
database250mers.kmer_distrib  inspect.txt
database300mers.kmer_distrib  ktaxonomy.tsv

sbatch scripts/kraken_sbatch.sh

Submitted batch job 33591789

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS,NodeList -j 33591789

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS        NodeList 
-------------------- -------- ---------- ---------- -------- ---------- ---------- --------------- 
          MedBioinfo       16       90Gn  COMPLETED      0:0   00:02:31                cpu-node-73 
               batch       16       90Gn  COMPLETED      0:0   00:02:31      7940K     cpu-node-73 
    kraken2_vs_abvhp       16       90Gn  COMPLETED      0:0   00:02:28  71848464K     cpu-node-73 

head analyses/kraken2/kraken_vs_abvhp.kraken

U	ERR6913158.1.1	0	149|150	0:115 |:| 0:116
U	ERR6913158.2.1	0	93|93	0:59 |:| 0:59
U	ERR6913158.3.1	0	151|149	0:117 |:| 0:115
U	ERR6913158.4.1	0	88|88	0:54 |:| 0:54
U	ERR6913158.5.1	0	151|149	0:117 |:| 0:115
U	ERR6913158.6.1	0	69|69	0:35 |:| 0:35
U	ERR6913158.7.1	0	151|149	0:117 |:| 0:115
U	ERR6913158.8.1	0	148|151	0:114 |:| 0:117
C	ERR6913158.9.1	1224	150|150	0:10 1224:5 0:101 |:| 0:103 1224:5 0:8
C	ERR6913158.10.1	2772066	129|129	0:17 2772066:2 0:76 |:| 0:76 2772066:2 0:17

head analyses/kraken2/kraken_vs_abvhp.kraken.report

 92.52	699069	699069	U	0	unclassified
  7.48	56538	98	R	1	root
  7.33	55360	121	R1	131567	  cellular organisms
  6.99	52796	1043	D	2	    Bacteria
  4.02	30374	652	P	1224	      Pseudomonadota
  2.05	15471	299	C	1236	        Gammaproteobacteria
  0.54	4109	1	O	72274	          Pseudomonadales
  0.54	4053	42	F	135621	            Pseudomonadaceae
  0.48	3602	966	G	286	              Pseudomonas
  0.14	1048	134	G1	196821	                unclassified Pseudomonas

ls -lh /shared/projects/2314_medbioinfo/hui/MedBioinfo23/data/sra_fastq

total 120M
-rw-rw----+ 1 huiyu huiyu 1.5M May 24 23:00 ERR6913156_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 1.5M May 24 23:00 ERR6913156_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu  45M May 24 23:03 ERR6913158_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu  46M May 24 23:03 ERR6913158_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 4.3M May 24 23:03 ERR6913168_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 4.4M May 24 23:03 ERR6913168_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 5.0M May 24 23:03 ERR6913169_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 5.0M May 24 23:03 ERR6913169_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 578K May 24 23:03 ERR6913252_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 585K May 24 23:03 ERR6913252_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 2.4M May 24 23:04 ERR6913254_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 2.4M May 24 23:04 ERR6913254_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 485K May 24 23:03 ERR6913264_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 491K May 24 23:03 ERR6913264_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 798K May 24 23:03 ERR6913265_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 800K May 24 23:03 ERR6913265_2.fastq.gz

sbatch scripts/kraken_sbatch.sh

Submitted batch job 33592127

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS,NodeList -j 33592127

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS        NodeList 
-------------------- -------- ---------- ---------- -------- ---------- ---------- --------------- 
          MedBioinfo       16       90Gn  COMPLETED      0:0   00:01:45                cpu-node-57 
               batch       16       90Gn  COMPLETED      0:0   00:01:45      7928K     cpu-node-57 
    kraken2_vs_abvhp       16       90Gn  COMPLETED      0:0   00:01:43  66994456K     cpu-node-57 

sbatch scripts/kraken_sbatch.sh

Submitted batch job 33592461

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS,NodeList -j 33592461

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS        NodeList 
-------------------- -------- ---------- ---------- -------- ---------- ---------- --------------- 
          MedBioinfo       16       90Gn  COMPLETED      0:0   00:02:56                cpu-node-73 
               batch       16       90Gn  COMPLETED      0:0   00:02:56      7932K     cpu-node-73 
    kraken2_vs_abvhp       16       90Gn  COMPLETED      0:0   00:02:55     65988M     cpu-node-73 

DAY3

kraken2 + bracken sbatch on a single sample

cd /shared/projects/2314_medbioinfo/hui/MedBioinfo23
pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

module load bracken

module load seqkit

bracken -help

/shared/ifbstor1/software/miniconda/envs/bracken-2.6.1/bin/bracken: illegal option -- h
Usage: bracken -d MY_DB -i INPUT -o OUTPUT -w OUTREPORT -r READ_LEN -l LEVEL -t THRESHOLD
  MY_DB          location of Kraken database
  INPUT          Kraken REPORT file to use for abundance estimation
  OUTPUT         file name for Bracken default output
  OUTREPORT      New Kraken REPORT output file with Bracken read estimates
  READ_LEN       read length to get all classifications for (default: 100)
  LEVEL          level to estimate abundance at [options: D,P,C,O,F,G,S,S1,etc] (default: S)
  THRESHOLD      number of reads required PRIOR to abundance estimation to perform reestimation (default: 0)

seqkit stats data/sra_fastq/ERR6913158_1.fastq.gz

file                                  format  type  num_seqs     sum_len  min_len  avg_len  max_len
data/sra_fastq/ERR6913158_1.fastq.gz  FASTQ   DNA    755,607  96,068,088       35    127.1      151

ls -lh data/sra_fastq

total 120M
-rw-rw----+ 1 huiyu huiyu 1.5M May 24 23:00 ERR6913156_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 1.5M May 24 23:00 ERR6913156_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu  45M May 24 23:03 ERR6913158_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu  46M May 24 23:03 ERR6913158_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 4.3M May 24 23:03 ERR6913168_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 4.4M May 24 23:03 ERR6913168_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 5.0M May 24 23:03 ERR6913169_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 5.0M May 24 23:03 ERR6913169_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 578K May 24 23:03 ERR6913252_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 585K May 24 23:03 ERR6913252_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 2.4M May 24 23:04 ERR6913254_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 2.4M May 24 23:04 ERR6913254_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 485K May 24 23:03 ERR6913264_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 491K May 24 23:03 ERR6913264_2.fastq.gz
-rw-rw----+ 1 huiyu huiyu 798K May 24 23:03 ERR6913265_1.fastq.gz
-rw-rw----+ 1 huiyu huiyu 800K May 24 23:03 ERR6913265_2.fastq.gz

sbatch scripts/kraken_bracken_sbatch.sh

Submitted batch job 33594008

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS,NodeList -j 33594008

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS        NodeList 
-------------------- -------- ---------- ---------- -------- ---------- ---------- --------------- 
          MedBioinfo       16       90Gn  COMPLETED      0:0   00:02:08                cpu-node-11 
               batch       16       90Gn  COMPLETED      0:0   00:02:08      7936K     cpu-node-11 
    kraken2_vs_abvhp       16       90Gn  COMPLETED      0:0   00:02:06  72704412K     cpu-node-11 
     kraken2_bracken       16       90Gn  COMPLETED      0:0   00:00:00      1232K     cpu-node-11 

workdir="/shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken"
datadir="/shared/projects/2314_medbioinfo/hui/MedBioinfo23/data/merged_pairs"
input_file1="/shared/projects/2314_medbioinfo/hui/MedBioinfo23/data/sra_fastq/ERR6913158_1.fastq.gz"
input_file2="/shared/projects/2314_medbioinfo/hui/MedBioinfo23/data/sra_fastq/ERR6913158_2.fastq.gz"
#accnum_file="/shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/huiyu_run_accession.txt"
output_file=${workdir}/kraken_vs_abvhp
#accnum_file="/shared/projects/2314_medbioinfo/hui/file_of_acc_nums.txt"
db="/shared/projects/2314_medbioinfo/kraken2/arch_bact_vir_hum_protoz_fung"
# srun --job-name=kraken2_bracken
bracken -d ${db} -i ${output_file}.ERR6913158.kraken.report -o ${output_file}.ERR6913158.bracken -w ${output_file}.ERR6913158.bracken.report

 >> Checking for Valid Options...
 >> Running Bracken 
      >> python src/est_abundance.py -i /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.kraken.report -o /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.bracken -k /shared/projects/2314_medbioinfo/kraken2/arch_bact_vir_hum_protoz_fung/database100mers.kmer_distrib -l S -t 10
PROGRAM START TIME: 05-30-2023 15:01:55
>> Checking report file: /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.kraken.report
BRACKEN SUMMARY (Kraken report: /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.kraken.report)
    >>> Threshold: 10 
    >>> Number of species in sample: 6628 
	  >> Number of species with reads > threshold: 645 
	  >> Number of species with reads < threshold: 5983 
    >>> Total reads in sample: 755607
	  >> Total reads kept at species level (reads > threshold): 25338
	  >> Total reads discarded (species reads < threshold): 18485
	  >> Reads distributed: 36789
	  >> Reads not distributed (eg. no species above threshold): 19749
	  >> Unclassified reads: 699069
BRACKEN OUTPUT PRODUCED: /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.bracken
PROGRAM END TIME: 05-30-2023 15:01:55
  Bracken complete.

head analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.bracken

name	taxonomy_id	taxonomy_lvl	kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads
Pseudomonas sp. FDAARGOS_380	2018067	S	224	128	352	0.00957
Pseudomonas sp. T1-3-2	2908006	S	115	7	122	0.00332
Pseudomonas sp. PIA16	2931382	S	43	2	45	0.00122
Pseudomonas sp. SDM007	2812000	S	15	15	30	0.00082
Pseudomonas sp. J380	2605424	S	13	34	47	0.00128
Pseudomonas sp. ATCC 13867	1294143	S	12	3	15	0.00041
Pseudomonas sp. L5B5	2883205	S	12	1	13	0.00035
Pseudomonas sp. LG1E9	2219057	S	11	3	14	0.00038
Pseudomonas sp. SCB32	2653853	S	11	2	13	0.00035

sort analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.bracken -t$'\t' -r -n -k 6 | head

Acinetobacter junii	40215	S	2292	485	2777	0.07548
Cutibacterium acnes	1747	S	2020	494	2514	0.06834
Vibrio fluvialis	676	S	1649	812	2461	0.06689
Burkholderia multivorans	87883	S	1227	252	1479	0.04020
Enterococcus cecorum	44008	S	1225	179	1404	0.03816
Homo sapiens	9606	S	1115	65	1180	0.03207
Pseudomonas aeruginosa	287	S	95	965	1060	0.02881
Corynebacterium propinquum	43769	S	807	94	901	0.02449
Shewanella algae	38313	S	680	163	843	0.02291
Stutzerimonas stutzeri	316	S	290	97	387	0.01052

Krona tool

ls /shared/projects/2314_medbioinfo/kraken2/KrakenTools

combine_kreports.py	 filter_bracken.out.py	LICENSE
combine_mpa.py		 fix_unmapped.py	make_kreport.py
DiversityTools		 kreport2krona.py	make_ktaxonomy.py
extract_kraken_reads.py  kreport2mpa.py		README.md

python /shared/projects/2314_medbioinfo/kraken2/KrakenTools/kreport2krona.py -h

usage: kreport2krona.py [-h] -r R_FILE -o O_FILE [--intermediate-ranks]
                        [--no-intermediate-ranks]

optional arguments:
  -h, --help            show this help message and exit
  -r R_FILE, --report-file R_FILE, --report R_FILE
                        Input kraken report file for converting
  -o O_FILE, --output O_FILE
                        Output krona-report file name
  --intermediate-ranks  Include non-traditional taxonomic ranks in output
  --no-intermediate-ranks
                        Do not include non-traditional taxonomic ranks in
                        output [default: no intermediate ranks]

mkdir analyses/krona

pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

# kraken_vs_abvhp.ERR6913158.bracken
ls ./analyses/kraken_bracken

kraken_vs_abvhp.ERR6913158.bracken
kraken_vs_abvhp.ERR6913158.bracken.report
kraken_vs_abvhp.ERR6913158.kraken
kraken_vs_abvhp.ERR6913158.kraken.report
slurm.33594008.4294967294.err
slurm.33594008.4294967294.out

kreport2krona="/shared/projects/2314_medbioinfo/kraken2/KrakenTools/kreport2krona.py"
python $kreport2krona -r ./analyses/kraken_bracken/kraken_vs_abvhp.ERR6913158.bracken.report -o ./analyses/krona/ERR6913158.krona

cat /shared/projects/2314_medbioinfo/kraken2/bin/ktImportText

#!/usr/bin/env perl

# Copyright © 2011, Battelle National Biodefense Institute (BNBI);
# all rights reserved. Authored by: Brian Ondov, Nicholas Bergman, and
# Adam Phillippy
#
# See the LICENSE.txt file included with this software for license information.


use strict;

BEGIN
{
	use File::Basename;
	use Cwd 'abs_path';
	use lib dirname(abs_path($0)) . "/../lib";
	use KronaTools;
}

setOption('out', 'text.krona.html');
setOption('name', 'all');

my @options =
qw(
	out
	name
	noMag
	combine
	url
);

getKronaOptions(@options);

if
(
	@ARGV < 1
)
{
	printUsage
	(
		'Creates a Krona chart from text files listing quantities and
lineages.',
		'text',
		'Tab-delimited text file. Each line should be a number followed by a
list of wedges to contribute to (starting from the highest level). If no wedges
are listed (and just a quantity is given), it will contribute to the top level.
If the same lineage is listed more than once, the values will be added.
Quantities can be omitted if -q is specified. Lines beginning with "#" will be
ignored.',
		0,
		1,
		\@options
	);
	
	exit 0;
}

my $tree = newTree();
my @datasetNames;
my $set = 0;

foreach my $input ( @ARGV )
{
	my ($fileName, $magFile, $name) = parseDataset($input);
	
	if ( ! getOption('combine') )
	{
		push @datasetNames, $name;
	}
	
	open INFILE, "<$fileName" or die $!;
	
	while ( <INFILE> )
	{
		if ( /^#/ )
		{
			next;
		}
		
		chomp;
		
		my @lineage = split /\t/;
		my $magnitude;
		
		if ( getOption('noMag') )
		{
			$magnitude = 1;
		}
		else
		{
			$magnitude = shift @lineage;
		}
		
		addByLineage($tree, $set, \@lineage, undef, $magnitude);
	}
	
	if ( ! getOption('combine') )
	{
		$set++;
	}
	
	close INFILE;
}

my @attributeNames =
(
	'magnitude',
	'magnitudeUnassigned'
);

my @attributeDisplayNames =
(
	'Total',
	'Unassigned'
);

writeTree
(
	$tree,
	\@attributeNames,
	\@attributeDisplayNames,
	\@datasetNames
);

/shared/projects/2314_medbioinfo/kraken2/bin/ktImportText -o ./analyses/krona/ERR6913158.krona.html ./analyses/krona/ERR6913158.krona

Writing ./analyses/krona/ERR6913158.krona.html...

cp -r analyses/kraken_bracken analyses/kraken_bracken_backup

sbatch scripts/kraken_2_krona.sh

Submitted batch job 33600060

sacct  --format=JobName%20,ReqCPUS,ReqMem,State,ExitCode,elapsed,MaxRSS,NodeList -j 33600060

             JobName  ReqCPUS     ReqMem      State ExitCode    Elapsed     MaxRSS        NodeList 
-------------------- -------- ---------- ---------- -------- ---------- ---------- --------------- 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:07:35                cpu-node-72 
               batch       16       80Gn  COMPLETED      0:0   00:07:35      7944K     cpu-node-72 
          ERR6913156       16       80Gn  COMPLETED      0:0   00:07:32  65705324K     cpu-node-72 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1148K     cpu-node-72 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1144K     cpu-node-72 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:06:39                cpu-node-74 
               batch       16       80Gn  COMPLETED      0:0   00:06:39      7940K     cpu-node-74 
          ERR6913158       16       80Gn  COMPLETED      0:0   00:06:35  72761412K     cpu-node-74 
             bracken       16       80Gn  COMPLETED      0:0   00:00:00      1140K     cpu-node-74 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:01      1140K     cpu-node-74 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:06:43                cpu-node-82 
               batch       16       80Gn  COMPLETED      0:0   00:06:43      7944K     cpu-node-82 
          ERR6913169       16       80Gn  COMPLETED      0:0   00:06:38  70817180K     cpu-node-82 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1152K     cpu-node-82 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1152K     cpu-node-82 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:07:18                cpu-node-39 
               batch       16       80Gn  COMPLETED      0:0   00:07:18      7960K     cpu-node-39 
          ERR6913264       16       80Gn  COMPLETED      0:0   00:07:15  68867768K     cpu-node-39 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1240K     cpu-node-39 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1232K     cpu-node-39 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:07:13                cpu-node-40 
               batch       16       80Gn  COMPLETED      0:0   00:07:13      7912K     cpu-node-40 
          ERR6913265       16       80Gn  COMPLETED      0:0   00:07:10  70276512K     cpu-node-40 
             bracken       16       80Gn  COMPLETED      0:0   00:00:00      1236K     cpu-node-40 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1232K     cpu-node-40 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:07:23                cpu-node-52 
               batch       16       80Gn  COMPLETED      0:0   00:07:23      7932K     cpu-node-52 
          ERR6913168       16       80Gn  COMPLETED      0:0   00:07:19  69047508K     cpu-node-52 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1232K     cpu-node-52 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1232K     cpu-node-52 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:07:34                cpu-node-11 
               batch       16       80Gn  COMPLETED      0:0   00:07:34      7920K     cpu-node-11 
          ERR6913252       16       80Gn  COMPLETED      0:0   00:07:33  72078732K     cpu-node-11 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1248K     cpu-node-11 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1248K     cpu-node-11 
        kraken2krona       16       80Gn  COMPLETED      0:0   00:05:43                cpu-node-70 
               batch       16       80Gn  COMPLETED      0:0   00:05:43      7940K     cpu-node-70 
          ERR6913254       16       80Gn  COMPLETED      0:0   00:05:39  71292320K     cpu-node-70 
             bracken       16       80Gn  COMPLETED      0:0   00:00:01      1152K     cpu-node-70 
             k2krona       16       80Gn  COMPLETED      0:0   00:00:00      1140K     cpu-node-70 

ls /shared/projects/2314_medbioinfo/kraken2/bin/ktImportText

/shared/projects/2314_medbioinfo/kraken2/bin/ktImportText

for file in analyses/kraken_vs_abvhp/*.krona
do
   /shared/projects/2314_medbioinfo/kraken2/bin/ktImportText -o $file.html $file
done

Writing analyses/kraken_vs_abvhp/ERR6913156.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913158.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913168.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913169.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913252.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913254.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913264.bracken.report.krona.html...
Writing analyses/kraken_vs_abvhp/ERR6913265.bracken.report.krona.html...

for file in analyses/kraken_vs_abvhp/*.krona
do
   sed -E 's/[a-z]//g' $file > $file_clean
   /shared/projects/2314_medbioinfo/kraken2/bin/ktImportText -o $file.html $file
done

rm -r analyses/kraken_vs_abvhp/*.krona_clean
rm -r analyses/kraken_vs_abvhp/*.krona_clean.html

for file in analyses/kraken_vs_abvhp/*.krona
do
   sed -e 's/[a-z]__//g' ${file} > ${file}_clean
   /shared/projects/2314_medbioinfo/kraken2/bin/ktImportText -o ${file}_clean.html ${file}_clean
done

Writing analyses/kraken_vs_abvhp/ERR6913156.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913158.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913168.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913169.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913252.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913254.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913264.bracken.report.krona_clean.html...
Writing analyses/kraken_vs_abvhp/ERR6913265.bracken.report.krona_clean.html...

/shared/projects/2314_medbioinfo/kraken2/bin/ktImportText -o analyses/kraken_vs_abvhp/all.html analyses/kraken_vs_abvhp/*.krona_clean

Writing analyses/kraken_vs_abvhp/all.html...

load bracken data into SQL long table

cd analyses/kraken_vs_abvhp

sacct -P --format=JobID%15,JobName%18,ReqCPUS,ReqMem,Timelimit,State,ExitCode,Start,elapsedRAW,CPUTimeRAW,MaxRSS,NodeList  -j 33600060 \
   | grep ERR > kraken2_full_FASTQ_vs_viral_sbatch_array.sacct

sqlite3 -batch -separator "|" /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
    ".import ./kraken2_full_FASTQ_vs_viral_sbatch_array.sacct kraken2_viral_resources_used"

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db "select * from kraken2_viral_resources_used where JobID like '33600060%';"

┌──────────────┬────────────┬─────────┬────────┬───────────┬───────────┬──────────┬─────────────────────┬────────────┬────────────┬───────────┬─────────────┐
│    JobID     │  JobName   │ ReqCPUS │ ReqMem │ Timelimit │   State   │ ExitCode │        Start        │ ElapsedRAW │ CPUTimeRAW │  MaxRSS   │  NodeList   │
├──────────────┼────────────┼─────────┼────────┼───────────┼───────────┼──────────┼─────────────────────┼────────────┼────────────┼───────────┼─────────────┤
│ 33600060_1.0 │ ERR6913156 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:32 │ 452        │ 7232       │ 65705324K │ cpu-node-72 │
│ 33600060_2.0 │ ERR6913158 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:32 │ 395        │ 6320       │ 72761412K │ cpu-node-74 │
│ 33600060_3.0 │ ERR6913169 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:32 │ 398        │ 6368       │ 70817180K │ cpu-node-82 │
│ 33600060_4.0 │ ERR6913264 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:32 │ 435        │ 6960       │ 68867768K │ cpu-node-39 │
│ 33600060_5.0 │ ERR6913265 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:33 │ 430        │ 6880       │ 70276512K │ cpu-node-40 │
│ 33600060_6.0 │ ERR6913168 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:15:33 │ 439        │ 7024       │ 69047508K │ cpu-node-52 │
│ 33600060_7.0 │ ERR6913252 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:16:31 │ 453        │ 7248       │ 72078732K │ cpu-node-11 │
│ 33600060_8.0 │ ERR6913254 │ 16      │ 80Gn   │           │ COMPLETED │ 0:0      │ 2023-05-31T11:18:02 │ 339        │ 5424       │ 71292320K │ cpu-node-70 │
└──────────────┴────────────┴─────────┴────────┴───────────┴───────────┴──────────┴─────────────────────┴────────────┴────────────┴───────────┴─────────────┘

multiQC add the kraken2 microbiome

cd /shared/projects/2314_medbioinfo/hui/MedBioinfo23

module load multiqc

multiqc --force --title "MultiQC" ../data/merged_pairs/ ./fastqc/ ./kraken_vs_abvhp/ ./blastn/

  /// ]8;id=301121;https://multiqc.info\MultiQC]8;;\ 🔍 | v1.13

|           multiqc | MultiQC Version v1.14 now available!
|           multiqc | Report title: MultiQC
|           multiqc | Search path : /shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/data/merged_pairs
|           multiqc | Search path : /shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/fastqc
|           multiqc | Search path : /shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/kraken_vs_abvhp
|           multiqc | Search path : /shared/ifbstor1/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/blastn
|         searching | ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 283/283  0mut/slurm.33590656.2.err1.err
|            kraken | Found 17 reports
|            fastqc | Found 16 reports
|             flash | Found 8 histogram reports
|           multiqc | Compressing plot data
|           multiqc | Report      : MultiQC_multiqc_report.html
|           multiqc | Data        : MultiQC_multiqc_report_data
|           multiqc | MultiQC complete

xargs -a ./analyses/huiyu_run_accession.txt -I{} sed -E 's/^/{}\t/' ./analyses/kraken_vs_abvhp/{}.bracken >> ./analyses/bracken_combined.tsv
head ./analyses/bracken_combined.tsv
echo "======="
grep -v "kraken_assigned_reads" ./analyses/bracken_combined.tsv > ./analyses/bracken_combined_no_headers.tsv
head ./analyses/bracken_combined_no_headers.tsv
echo "======="
tail ./analyses/bracken_combined_no_headers.tsv
echo "======="
wc -l ./analyses/bracken_combined_no_headers.tsv

ERR6913156	name	taxonomy_id	taxonomy_lvl	kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads
ERR6913156	Cutibacterium acnes	1747	S	175	12	187	0.21347
ERR6913156	Corynebacterium kefirresidentii	1979527	S	60	26	86	0.09817
ERR6913156	Lactobacillus crispatus	47770	S	35	9	44	0.05023
ERR6913156	Dolosigranulum pigrum	29394	S	29	4	33	0.03767
ERR6913156	Staphylococcus saprophyticus	29385	S	16	21	37	0.04224
ERR6913156	Acinetobacter junii	40215	S	67	66	133	0.15183
ERR6913156	Vibrio fluvialis	676	S	12	9	21	0.02397
ERR6913156	Schlegelella aquatica	376175	S	10	12	22	0.02511
ERR6913156	Homo sapiens	9606	S	219	7	226	0.25799
=======
ERR6913156	Cutibacterium acnes	1747	S	175	12	187	0.21347
ERR6913156	Corynebacterium kefirresidentii	1979527	S	60	26	86	0.09817
ERR6913156	Lactobacillus crispatus	47770	S	35	9	44	0.05023
ERR6913156	Dolosigranulum pigrum	29394	S	29	4	33	0.03767
ERR6913156	Staphylococcus saprophyticus	29385	S	16	21	37	0.04224
ERR6913156	Acinetobacter junii	40215	S	67	66	133	0.15183
ERR6913156	Vibrio fluvialis	676	S	12	9	21	0.02397
ERR6913156	Schlegelella aquatica	376175	S	10	12	22	0.02511
ERR6913156	Homo sapiens	9606	S	219	7	226	0.25799
ERR6913156	Aspergillus chevalieri	182096	S	82	1	83	0.09475
=======
ERR6913254	Thalassiosira pseudonana	35128	S	383	26	409	0.05449
ERR6913254	Toxoplasma gondii	5811	S	22	25	47	0.00626
ERR6913254	Bigelowiella natans	227086	S	17	0	17	0.00226
ERR6913254	Malassezia restricta	76775	S	53	8	61	0.00813
ERR6913254	Homo sapiens	9606	S	80	28	108	0.01439
ERR6913254	Cryptomonas paramecium	2898	S	19	7	26	0.00346
ERR6913254	Guillardia theta	55529	S	19	10	29	0.00386
ERR6913254	Natronomonas moolapensis	416273	S	25	14	39	0.00520
ERR6913254	Human mastadenovirus C	129951	S	38	0	38	0.00506
ERR6913254	Severe acute respiratory syndrome-related coronavirus	694009	S	17	0	17	0.00226
=======
824 ./analyses/bracken_combined_no_headers.tsv

sqlite3 /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'CREATE TABLE IF NOT EXISTS "bracken_abundances_long"(
  "run_accession" TEXT,
  "taxon_name" TEXT,
  "taxonomy_id" INTEGER,
  "taxonomy_lvl" TEXT,
  "kraken_assigned_reads" INTEGER,
  "added_reads" INTEGER,
  "new_est_reads" INTEGER,
  "fraction_total_reads" REAL,
  PRIMARY_KEY:run_accession, taxonomy_id);"

sqlite3 -batch -tabs /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'.import /shared/projects/2314_medbioinfo/hui/MedBioinfo23/analyses/bracken_combined_no_headers.tsv bracken_abundances_long'

cut -f1 analyses/bracken_combined_no_headers.tsv | sort | uniq -c

     10 ERR6913156
    645 ERR6913158
     27 ERR6913168
     26 ERR6913169
     12 ERR6913252
     74 ERR6913254
     10 ERR6913264
     20 ERR6913265

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'.table'

CtValues                          braken_abundances_long          
ENARunTable                       kraken2_viral_resources_used    
SampleOverviews                   kraken2_viral_resources_used_2  
SraRunTable                       kraken2_viral_resources_used_bak
bioinformaticians                 sample2bioinformatician         
blastn_viral_resources_used       sample_annot                    
bracken_abundances_long           sample_annot_all                

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT username, run_accession, count(*)
FROM (bracken_abundances_long abu left join sample_annot using(run_accession))
    left join sample2bioinformatician sb using(patient_code) group by username,run_accession order by username;'

username         run_accession  count(*)
---------------  -------------  --------
                 ERR6913107     40      
                 ERR6913139     621     
                 ERR6913145     270     
                 ERR6913146     175     
                 ERR6913203     29      
                 ERR6913235     1227    
                 ERR6913241     999     
                 ERR6913242     1973    
aarzoomand       ERR6913305     566     
aarzoomand       ERR6913306     277     
aarzoomand       ERR6913307     329     
aarzoomand       ERR6913308     331     
aarzoomand       ERR6913334     353     
aarzoomand       ERR6913335     355     
aarzoomand       ERR6913336     237     
aarzoomand       ERR6913337     284     
akarlsson        ERR6913104     645     
akarlsson        ERR6913131     797     
akarlsson        ERR6913132     1506    
akarlsson        ERR6913133     2196    
akarlsson        ERR6913134     211     
akarlsson        ERR6913200     826     
akarlsson        ERR6913227     1114    
akarlsson        ERR6913228     2007    
akarlsson        ERR6913229     1239    
akarlsson        ERR6913230     947     
eahlberg         ERR6913126     614     
eahlberg         ERR6913222     417     
eahlberg         ERR6913295     256     
eahlberg         ERR6913298     201     
eahlberg         ERR6913299     275     
eahlberg         ERR6913324     256     
eahlberg         ERR6913327     497     
eahlberg         ERR6913328     609     
elahtinen        ERR6913106     251     
elahtinen        ERR6913121     114     
elahtinen        ERR6913135     428     
elahtinen        ERR6913202     254     
elahtinen        ERR6913217     136     
elahtinen        ERR6913231     827     
elahtinen        ERR6913297     703     
elahtinen        ERR6913326     667     
huiyu            ERR6913156     10      
huiyu            ERR6913158     645     
huiyu            ERR6913168     27      
huiyu            ERR6913169     26      
huiyu            ERR6913252     12      
huiyu            ERR6913254     74      
huiyu            ERR6913264     10      
huiyu            ERR6913265     20      
lhohmann         ERR6913183     1657    
lhohmann         ERR6913184     1111    
lhohmann         ERR6913185     212     
lhohmann         ERR6913186     1585    
lhohmann         ERR6913279     714     
lhohmann         ERR6913280     557     
lhohmann         ERR6913281     1367    
lhohmann         ERR6913282     1784    
linastep         ERR6913147     384     
linastep         ERR6913154     10      
linastep         ERR6913157     32      
linastep         ERR6913165     37      
linastep         ERR6913243     665     
linastep         ERR6913250     20      
linastep         ERR6913253     21      
linastep         ERR6913261     7       
llindquist       ERR6913140     663     
llindquist       ERR6913191     206     
llindquist       ERR6913193     290     
llindquist       ERR6913195     559     
llindquist       ERR6913236     901     
llindquist       ERR6913287     723     
llindquist       ERR6913289     494     
llindquist       ERR6913291     645     
mmiari           ERR6913102     62      
mmiari           ERR6913187     280     
mmiari           ERR6913188     1415    
mmiari           ERR6913189     1811    
mmiari           ERR6913283     373     
mmiari           ERR6913284     1411    
mmiari           ERR6913285     1593    
mtronstad        ERR6913101     754     
mtronstad        ERR6913179     1001    
mtronstad        ERR6913180     1906    
mtronstad        ERR6913181     706     
mtronstad        ERR6913182     1191    
mtronstad        ERR6913197     1056    
mtronstad        ERR6913275     410     
mtronstad        ERR6913276     4968    
mtronstad        ERR6913277     1560    
mtronstad        ERR6913278     1020    
phingamp         ERR6913174     386     
phingamp         ERR6913175     1188    
phingamp         ERR6913176     4092    
phingamp         ERR6913177     4789    
phingamp         ERR6913178     3322    
phingamp         ERR6913270     1011    
phingamp         ERR6913271     1005    
phingamp         ERR6913272     143     
phingamp         ERR6913273     61      
phingamp         ERR6913274     88      
pkalogeropoulos  ERR6913114     57      
pkalogeropoulos  ERR6913123     114     
pkalogeropoulos  ERR6913124     72      
pkalogeropoulos  ERR6913155     13      
pkalogeropoulos  ERR6913210     90      
pkalogeropoulos  ERR6913219     136     
pkalogeropoulos  ERR6913220     59      
pkalogeropoulos  ERR6913251     12      
rfeeney          ERR6913312     1021    
rfeeney          ERR6913314     319     
rfeeney          ERR6913315     650     
rfeeney          ERR6913316     828     
rfeeney          ERR6913341     1122    
rfeeney          ERR6913343     702     
rfeeney          ERR6913344     846     
rfeeney          ERR6913345     1050    
rgrochowski      ERR6913112     81      
rgrochowski      ERR6913113     153     
rgrochowski      ERR6913122     459     
rgrochowski      ERR6913208     37      
rgrochowski      ERR6913209     33      
rgrochowski      ERR6913218     182     
rgrochowski      ERR6913320     1313    
rgrochowski      ERR6913349     480     
rpotter          ERR6913108     22      
rpotter          ERR6913116     22      
rpotter          ERR6913118     141     
rpotter          ERR6913136     530     
rpotter          ERR6913204     24      
rpotter          ERR6913212     7       
rpotter          ERR6913214     63      
rpotter          ERR6913232     1209    
snarrowe         ERR6913103     13      
snarrowe         ERR6913111     7       
snarrowe         ERR6913115     1       
snarrowe         ERR6913117     8       
snarrowe         ERR6913128     237     
snarrowe         ERR6913199     3       
snarrowe         ERR6913207     3       
snarrowe         ERR6913211     4       
snarrowe         ERR6913213     5       
snarrowe         ERR6913224     143     

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT * FROM bracken_abundances_long LIMIT 5;'

run_accession  taxon_name                        taxonomy_id  taxonomy_lvl  kraken_assigned_reads  added_reads  new_est_reads  fraction_total_reads
-------------  --------------------------------  -----------  ------------  ---------------------  -----------  -------------  --------------------
ERR6913112     Streptococcus oralis              1303         S             315                    139          454            0.04101             
ERR6913112     Streptococcus sp. LPB0220         2610896      S             64                     14           78             0.00705             
ERR6913112     Streptococcus sp. HSISM1          1316408      S             50                     10           60             0.00542             
ERR6913112     Streptococcus sp. oral taxon 064  712624       S             14                     21           35             0.00316             
ERR6913112     Streptococcus sp. oral taxon 061  712623       S             11                     1            12             0.00108             

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT sample_name,total_reads,nonhost_reads FROM SampleOverviews LIMIT 5;'

┌───────────────────┬─────────────┬───────────────┐
│    sample_name    │ total_reads │ nonhost_reads │
├───────────────────┼─────────────┼───────────────┤
│ P011_DNA_S39_L001 │ 27630988    │ 102524        │
│ P312_DNA_S28_L001 │ 16206168    │ 151202        │
│ P306_DNA_S85_L001 │ 20868084    │ 539076        │
│ P276_DNA_S26_L001 │ 26596212    │ 729230        │
│ P272_DNA_S40_L001 │ 24205196    │ 397186        │
└───────────────────┴─────────────┴───────────────┘

cd ..
pwd

/shared/projects/2314_medbioinfo/hui/MedBioinfo23

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT run_accession, sum(new_est_reads) AS total_reads,sum(fraction_total_reads) AS total_fraction, count(*) AS nb FROM bracken_abundances_long GROUP BY run_accession;'

┌───────────────┬─────────────┬───────────────────┬──────┐
│ run_accession │ total_reads │  total_fraction   │  nb  │
├───────────────┼─────────────┼───────────────────┼──────┤
│ ERR6913101    │ 120450      │ 0.996980000000002 │ 754  │
│ ERR6913102    │ 6547        │ 0.995269999999999 │ 62   │
│ ERR6913103    │ 798         │ 0.99008           │ 13   │
│ ERR6913104    │ 167654      │ 0.998400000000002 │ 645  │
│ ERR6913106    │ 365105      │ 0.99967           │ 251  │
│ ERR6913107    │ 6922        │ 0.9977            │ 39   │
│ ERR6913108    │ 2224        │ 0.9964            │ 22   │
│ ERR6913109    │ 8030        │ 0.99193           │ 148  │
│ ERR6913111    │ 259         │ 0.98855           │ 7    │
│ ERR6913112    │ 11038       │ 0.99706           │ 81   │
│ ERR6913113    │ 10511       │ 0.992139999999999 │ 153  │
│ ERR6913114    │ 8695        │ 0.99702           │ 57   │
│ ERR6913115    │ 79          │ 1.0               │ 1    │
│ ERR6913116    │ 2085        │ 0.99427           │ 22   │
│ ERR6913117    │ 588         │ 0.99325           │ 8    │
│ ERR6913118    │ 37316       │ 0.99824           │ 141  │
│ ERR6913120    │ 4534        │ 0.99409           │ 56   │
│ ERR6913121    │ 9853        │ 0.994180000000001 │ 114  │
│ ERR6913122    │ 174203      │ 0.998660000000001 │ 459  │
│ ERR6913123    │ 18415       │ 0.99718           │ 114  │
│ ERR6913124    │ 19245       │ 0.99848           │ 72   │
│ ERR6913125    │ 1372        │ 0.99493           │ 13   │
│ ERR6913126    │ 55648       │ 0.994610000000001 │ 614  │
│ ERR6913128    │ 413755      │ 0.999729999999999 │ 237  │
│ ERR6913131    │ 925278      │ 1.00044999999999  │ 797  │
│ ERR6913132    │ 695110      │ 0.999159999999985 │ 1506 │
│ ERR6913133    │ 513470      │ 0.997829999999991 │ 2196 │
│ ERR6913134    │ 68210       │ 0.998759999999999 │ 211  │
│ ERR6913135    │ 914437      │ 0.999749999999999 │ 428  │
│ ERR6913136    │ 869839      │ 0.999609999999999 │ 530  │
│ ERR6913137    │ 850617      │ 0.999600000000001 │ 819  │
│ ERR6913138    │ 821002      │ 1.00005999999999  │ 1381 │
│ ERR6913139    │ 758566      │ 0.999589999999999 │ 620  │
│ ERR6913140    │ 782977      │ 0.999589999999999 │ 663  │
│ ERR6913145    │ 212601      │ 0.99944           │ 269  │
│ ERR6913146    │ 149287      │ 0.999420000000001 │ 174  │
│ ERR6913147    │ 836305      │ 0.99985           │ 384  │
│ ERR6913154    │ 15464       │ 0.99981           │ 10   │
│ ERR6913155    │ 969         │ 0.99281           │ 13   │
│ ERR6913156    │ 872         │ 0.99543           │ 10   │
│ ERR6913157    │ 2881        │ 0.99447           │ 32   │
│ ERR6913158    │ 36491       │ 0.991890000000002 │ 645  │
│ ERR6913159    │ 719         │ 0.99308           │ 9    │
│ ERR6913161    │ 6543        │ 0.99249           │ 105  │
│ ERR6913164    │ 5041        │ 0.98919           │ 116  │
│ ERR6913165    │ 6626        │ 0.99712           │ 37   │
│ ERR6913166    │ 9277        │ 0.99349           │ 118  │
│ ERR6913168    │ 5153        │ 0.99767           │ 27   │
│ ERR6913169    │ 5120        │ 0.99747           │ 26   │
│ ERR6913170    │ 2507        │ 0.99602           │ 29   │
│ ERR6913171    │ 10870       │ 0.99662           │ 81   │
│ ERR6913172    │ 54115       │ 0.98870000000001  │ 1348 │
│ ERR6913173    │ 4335        │ 0.99767           │ 23   │
│ ERR6913174    │ 21023       │ 0.99102           │ 386  │
│ ERR6913175    │ 35561       │ 0.984209999999999 │ 1188 │
│ ERR6913176    │ 113264      │ 0.982000000000004 │ 4092 │
│ ERR6913177    │ 144762      │ 0.982870000000005 │ 4789 │
│ ERR6913178    │ 84008       │ 0.982620000000004 │ 3322 │
│ ERR6913179    │ 664245      │ 0.999719999999995 │ 1001 │
│ ERR6913180    │ 682845      │ 0.998659999999984 │ 1906 │
│ ERR6913181    │ 967396      │ 1.00030999999999  │ 706  │
│ ERR6913182    │ 686889      │ 0.999359999999983 │ 1191 │
│ ERR6913183    │ 801894      │ 0.999449999999961 │ 1656 │
│ ERR6913184    │ 720548      │ 0.99966999999998  │ 1110 │
│ ERR6913185    │ 68208       │ 0.99879           │ 211  │
│ ERR6913186    │ 765749      │ 0.999589999999977 │ 1584 │
│ ERR6913187    │ 93044       │ 0.99875           │ 280  │
│ ERR6913188    │ 795467      │ 1.00018999999998  │ 1415 │
│ ERR6913189    │ 680246      │ 0.998559999999966 │ 1811 │
│ ERR6913191    │ 93173       │ 0.999             │ 206  │
│ ERR6913193    │ 341647      │ 0.999579999999999 │ 290  │
│ ERR6913195    │ 621320      │ 0.999680000000001 │ 559  │
│ ERR6913197    │ 222126      │ 0.997699999999999 │ 1056 │
│ ERR6913199    │ 580         │ 1.0               │ 3    │
│ ERR6913200    │ 633562      │ 0.999439999999998 │ 826  │
│ ERR6913202    │ 606099      │ 0.999770000000001 │ 254  │
│ ERR6913203    │ 5996        │ 0.9977            │ 28   │
│ ERR6913204    │ 14090       │ 0.99915           │ 24   │
│ ERR6913205    │ 381483      │ 0.99925           │ 687  │
│ ERR6913207    │ 165         │ 0.98802           │ 3    │
│ ERR6913208    │ 45738       │ 0.99964           │ 37   │
│ ERR6913209    │ 3169        │ 0.99432           │ 33   │
│ ERR6913210    │ 14819       │ 0.99701           │ 90   │
│ ERR6913211    │ 521         │ 1.00001           │ 4    │
│ ERR6913212    │ 627         │ 0.99523           │ 7    │
│ ERR6913213    │ 242         │ 0.99588           │ 5    │
│ ERR6913214    │ 11758       │ 0.99721           │ 63   │
│ ERR6913215    │ 10646       │ 0.9967            │ 74   │
│ ERR6913216    │ 10008       │ 0.99889           │ 21   │
│ ERR6913217    │ 30273       │ 0.99796           │ 136  │
│ ERR6913218    │ 89527       │ 0.99909           │ 182  │
│ ERR6913219    │ 271498      │ 0.99972           │ 136  │
│ ERR6913220    │ 37159       │ 0.99918           │ 59   │
│ ERR6913221    │ 5897        │ 0.99845           │ 23   │
│ ERR6913222    │ 576327      │ 0.999709999999999 │ 417  │
│ ERR6913224    │ 117677      │ 0.99944           │ 143  │
│ ERR6913227    │ 1185215     │ 0.99993999999999  │ 1114 │
│ ERR6913228    │ 822575      │ 1.00001999999997  │ 2007 │
│ ERR6913229    │ 1128230     │ 1.00001999999999  │ 1239 │
│ ERR6913230    │ 235388      │ 0.998479999999996 │ 947  │
│ ERR6913231    │ 1137573     │ 0.999539999999992 │ 827  │
│ ERR6913232    │ 1287895     │ 0.99941999999999  │ 1209 │
│ ERR6913233    │ 1471682     │ 0.999309999999977 │ 1614 │
│ ERR6913234    │ 1215969     │ 0.999429999999986 │ 1334 │
│ ERR6913235    │ 928408      │ 0.99938           │ 1226 │
│ ERR6913236    │ 1425266     │ 0.999869999999996 │ 901  │
│ ERR6913241    │ 1180170     │ 0.999539999999996 │ 998  │
│ ERR6913242    │ 696544      │ 0.998490000000002 │ 1972 │
│ ERR6913243    │ 1273155     │ 0.999759999999995 │ 665  │
│ ERR6913250    │ 83257       │ 0.99988           │ 20   │
│ ERR6913251    │ 998         │ 0.99502           │ 12   │
│ ERR6913252    │ 7546        │ 0.99933           │ 12   │
│ ERR6913253    │ 2468        │ 0.99596           │ 21   │
│ ERR6913254    │ 7471        │ 0.995350000000001 │ 74   │
│ ERR6913255    │ 754         │ 0.99603           │ 5    │
│ ERR6913257    │ 14486       │ 0.99781           │ 68   │
│ ERR6913260    │ 1645        │ 0.99516           │ 24   │
│ ERR6913261    │ 719         │ 0.99585           │ 7    │
│ ERR6913262    │ 12138       │ 0.99919           │ 21   │
│ ERR6913264    │ 5010        │ 0.9994            │ 10   │
│ ERR6913265    │ 1698        │ 0.99473           │ 20   │
│ ERR6913266    │ 1883        │ 0.9968            │ 18   │
│ ERR6913267    │ 4922        │ 0.99431           │ 57   │
│ ERR6913268    │ 45274       │ 0.988810000000001 │ 1064 │
│ ERR6913269    │ 11949       │ 0.99983           │ 7    │
│ ERR6913270    │ 49731       │ 0.991479999999999 │ 1011 │
│ ERR6913271    │ 473521      │ 0.998809999999997 │ 1005 │
│ ERR6913272    │ 23210       │ 0.997180000000001 │ 143  │
│ ERR6913273    │ 1956        │ 0.98297           │ 61   │
│ ERR6913274    │ 4753        │ 0.99164           │ 88   │
│ ERR6913275    │ 266886      │ 0.999210000000001 │ 410  │
│ ERR6913276    │ 906867      │ 0.999619999999931 │ 4968 │
│ ERR6913277    │ 1231583     │ 0.999619999999971 │ 1560 │
│ ERR6913278    │ 1273587     │ 0.999619999999994 │ 1020 │
│ ERR6913279    │ 1453824     │ 0.999759999999994 │ 713  │
│ ERR6913280    │ 1436016     │ 0.999749999999999 │ 556  │
│ ERR6913281    │ 1094958     │ 0.999869999999993 │ 1366 │
│ ERR6913282    │ 1091047     │ 1.00014999999997  │ 1783 │
│ ERR6913283    │ 110183      │ 0.99839           │ 373  │
│ ERR6913284    │ 925913      │ 1.00047999999998  │ 1411 │
│ ERR6913285    │ 883552      │ 1.00014999999997  │ 1593 │
│ ERR6913287    │ 1044802     │ 0.99976           │ 723  │
│ ERR6913289    │ 1008634     │ 0.999679999999998 │ 494  │
│ ERR6913291    │ 1202323     │ 0.999399999999996 │ 645  │
│ ERR6913293    │ 180024      │ 0.9984            │ 627  │
│ ERR6913294    │ 521475      │ 0.999230000000001 │ 644  │
│ ERR6913295    │ 26672       │ 0.995650000000001 │ 256  │
│ ERR6913296    │ 566661      │ 0.998909999999997 │ 1158 │
│ ERR6913297    │ 708138      │ 0.99958           │ 703  │
│ ERR6913298    │ 42228       │ 0.99792           │ 201  │
│ ERR6913299    │ 132195      │ 0.999049999999999 │ 275  │
│ ERR6913302    │ 170133      │ 0.999040000000001 │ 420  │
│ ERR6913304    │ 312336      │ 0.999840000000001 │ 155  │
│ ERR6913305    │ 644761      │ 0.999629999999999 │ 566  │
│ ERR6913306    │ 255016      │ 0.999450000000001 │ 277  │
│ ERR6913307    │ 423253      │ 0.99956           │ 329  │
│ ERR6913308    │ 774422      │ 0.999849999999999 │ 331  │
│ ERR6913312    │ 194002      │ 0.998549999999997 │ 1021 │
│ ERR6913313    │ 822077      │ 0.99983           │ 314  │
│ ERR6913314    │ 1042806     │ 0.999859999999996 │ 319  │
│ ERR6913315    │ 159602      │ 0.998430000000001 │ 650  │
│ ERR6913316    │ 122645      │ 0.997480000000001 │ 828  │
│ ERR6913320    │ 522400      │ 0.998389999999999 │ 1313 │
│ ERR6913322    │ 1184330     │ 0.999889999999998 │ 475  │
│ ERR6913323    │ 828544      │ 0.99959           │ 711  │
│ ERR6913324    │ 26672       │ 0.995650000000001 │ 256  │
│ ERR6913325    │ 660086      │ 0.999249999999989 │ 1271 │
│ ERR6913326    │ 902722      │ 0.999670000000001 │ 667  │
│ ERR6913327    │ 462986      │ 0.999439999999999 │ 497  │
│ ERR6913328    │ 151456      │ 0.998180000000001 │ 609  │
│ ERR6913331    │ 211684      │ 0.998329999999998 │ 752  │
│ ERR6913333    │ 885904      │ 0.999899999999991 │ 542  │
│ ERR6913334    │ 774382      │ 0.99972           │ 353  │
│ ERR6913335    │ 727340      │ 0.99959           │ 355  │
│ ERR6913336    │ 314974      │ 0.99965           │ 237  │
│ ERR6913337    │ 1471167     │ 0.99989           │ 284  │
│ ERR6913341    │ 997919      │ 1.00039999999999  │ 1122 │
│ ERR6913342    │ 1835085     │ 1.00012           │ 437  │
│ ERR6913343    │ 1714397     │ 0.999889999999995 │ 702  │
│ ERR6913344    │ 1139978     │ 0.999689999999992 │ 846  │
│ ERR6913345    │ 1108074     │ 0.99961999999999  │ 1050 │
│ ERR6913349    │ 1504874     │ 0.999939999999998 │ 480  │
└───────────────┴─────────────┴───────────────────┴──────┘

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT run_accession,taxon_name,taxonomy_id,new_est_reads,fraction_total_reads AS fraction
 FROM bracken_abundances_long
 WHERE taxon_name LIKE "%corona%"
 ORDER BY fraction_total_reads DESC;'

┌───────────────┬───────────────────────────────────────────────────────┬─────────────┬───────────────┬──────────┐
│ run_accession │                      taxon_name                       │ taxonomy_id │ new_est_reads │ fraction │
├───────────────┼───────────────────────────────────────────────────────┼─────────────┼───────────────┼──────────┤
│ ERR6913216    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 7797          │ 0.77822  │
│ ERR6913199    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 439           │ 0.7569   │
│ ERR6913221    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 4360          │ 0.73823  │
│ ERR6913210    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 6142          │ 0.41324  │
│ ERR6913214    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 4573          │ 0.38784  │
│ ERR6913211    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 150           │ 0.28791  │
│ ERR6913215    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 2365          │ 0.22142  │
│ ERR6913203    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 1318          │ 0.2193   │
│ ERR6913217    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5938          │ 0.19576  │
│ ERR6913204    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 2468          │ 0.17501  │
│ ERR6913219    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 11656         │ 0.04292  │
│ ERR6913213    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 10            │ 0.04115  │
│ ERR6913197    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 8980          │ 0.04034  │
│ ERR6913212    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 23            │ 0.03651  │
│ ERR6913261    │ Human coronavirus NL63                                │ 277944      │ 21            │ 0.02909  │
│ ERR6913208    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 968           │ 0.02116  │
│ ERR6913220    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 736           │ 0.01979  │
│ ERR6913218    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 1532          │ 0.0171   │
│ ERR6913252    │ Human coronavirus HKU1                                │ 290028      │ 80            │ 0.01059  │
│ ERR6913121    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 77            │ 0.00777  │
│ ERR6913209    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 24            │ 0.00753  │
│ ERR6913200    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 4760          │ 0.00751  │
│ ERR6913327    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 1484          │ 0.0032   │
│ ERR6913267    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 12            │ 0.00242  │
│ ERR6913254    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 17            │ 0.00226  │
│ ERR6913330    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 879           │ 0.00159  │
│ ERR6913268    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 64            │ 0.0014   │
│ ERR6913126    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 76            │ 0.00136  │
│ ERR6913101    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 128           │ 0.00106  │
│ ERR6913329    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 307           │ 0.00102  │
│ ERR6913326    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 828           │ 0.00092  │
│ ERR6913328    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 104           │ 0.00069  │
│ ERR6913275    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 168           │ 0.00063  │
│ ERR6913122    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 92            │ 0.00053  │
│ ERR6913315    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 84            │ 0.00053  │
│ ERR6913331    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 100           │ 0.00047  │
│ ERR6913305    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 298           │ 0.00046  │
│ ERR6913293    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 79            │ 0.00044  │
│ ERR6913322    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 517           │ 0.00044  │
│ ERR6913226    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 428           │ 0.00035  │
│ ERR6913230    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 76            │ 0.00032  │
│ ERR6913233    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 444           │ 0.0003   │
│ ERR6913205    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 87            │ 0.00023  │
│ ERR6913312    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 39            │ 0.0002   │
│ ERR6913295    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5             │ 0.00019  │
│ ERR6913324    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5             │ 0.00019  │
│ ERR6913223    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 105           │ 0.00019  │
│ ERR6913104    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 29            │ 0.00017  │
│ ERR6913334    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 101           │ 0.00013  │
│ ERR6913202    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 55            │ 9.0e-05  │
│ ERR6913332    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 90            │ 8.0e-05  │
│ ERR6913242    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 50            │ 7.0e-05  │
│ ERR6913333    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 43            │ 5.0e-05  │
│ ERR6913276    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 26            │ 3.0e-05  │
│ ERR6913276    │ Pseudomonas coronafaciens                             │ 53409       │ 21            │ 2.0e-05  │
│ ERR6913222    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 13            │ 2.0e-05  │
│ ERR6913306    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 6             │ 2.0e-05  │
│ ERR6913345    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 26            │ 2.0e-05  │
│ ERR6913325    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 10            │ 2.0e-05  │
│ ERR6913313    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 13            │ 2.0e-05  │
│ ERR6913342    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 34            │ 2.0e-05  │
│ ERR6913323    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 20            │ 2.0e-05  │
│ ERR6913271    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 6             │ 1.0e-05  │
│ ERR6913307    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5             │ 1.0e-05  │
│ ERR6913343    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 11            │ 1.0e-05  │
│ ERR6913228    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5             │ 1.0e-05  │
│ ERR6913196    │ Pseudomonas coronafaciens                             │ 53409       │ 7             │ 1.0e-05  │
│ ERR6913344    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 5             │ 0.0      │
│ ERR6913194    │ Pseudomonas coronafaciens                             │ 53409       │ 2             │ 0.0      │
│ ERR6913225    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 1             │ 0.0      │
│ ERR6913290    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 2             │ 0.0      │
│ ERR6913292    │ Severe acute respiratory syndrome-related coronavirus │ 694009      │ 2             │ 0.0      │
└───────────────┴───────────────────────────────────────────────────────┴─────────────┴───────────────┴──────────┘

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT run_accession,taxon_name,new_est_reads,fraction_total_reads AS fraction
 FROM bracken_abundances_long
 WHERE taxon_name LIKE "%human%"
 ORDER BY fraction_total_reads DESC;'

┌───────────────┬──────────────────────────┬───────────────┬──────────┐
│ run_accession │        taxon_name        │ new_est_reads │ fraction │
├───────────────┼──────────────────────────┼───────────────┼──────────┤
│ ERR6913261    │ Human coronavirus NL63   │ 21            │ 0.02909  │
│ ERR6913109    │ Human betaherpesvirus 6B │ 161           │ 0.01989  │
│ ERR6913252    │ Human coronavirus HKU1   │ 80            │ 0.01059  │
│ ERR6913260    │ Human mastadenovirus C   │ 11            │ 0.00665  │
│ ERR6913254    │ Human mastadenovirus C   │ 38            │ 0.00506  │
│ ERR6913273    │ Human mastadenovirus C   │ 9             │ 0.00452  │
│ ERR6913267    │ Human mastadenovirus C   │ 15            │ 0.00303  │
│ ERR6913268    │ Human mastadenovirus C   │ 136           │ 0.00297  │
│ ERR6913272    │ Human betaherpesvirus 6B │ 69            │ 0.00296  │
│ ERR6913187    │ Human betaherpesvirus 6B │ 169           │ 0.00181  │
│ ERR6913274    │ Human mastadenovirus C   │ 7             │ 0.00146  │
│ ERR6913283    │ Human betaherpesvirus 6B │ 159           │ 0.00144  │
│ ERR6913272    │ Human mastadenovirus C   │ 28            │ 0.0012   │
│ ERR6913112    │ Human gammaherpesvirus 4 │ 12            │ 0.00108  │
│ ERR6913210    │ Human mastadenovirus C   │ 16            │ 0.00108  │
│ ERR6913176    │ Human betaherpesvirus 6B │ 107           │ 0.00093  │
│ ERR6913276    │ Human mastadenovirus C   │ 687           │ 0.00076  │
│ ERR6913180    │ Bacteroides humanifaecis │ 356           │ 0.00052  │
│ ERR6913295    │ Human mastadenovirus C   │ 14            │ 0.00052  │
│ ERR6913324    │ Human mastadenovirus C   │ 14            │ 0.00052  │
│ ERR6913106    │ Human gammaherpesvirus 4 │ 179           │ 0.00049  │
│ ERR6913270    │ Human mastadenovirus C   │ 23            │ 0.00046  │
│ ERR6913306    │ Human gammaherpesvirus 4 │ 111           │ 0.00044  │
│ ERR6913217    │ Human mastadenovirus C   │ 13            │ 0.00043  │
│ ERR6913328    │ Human mastadenovirus C   │ 44            │ 0.00029  │
│ ERR6913323    │ Human mastadenovirus C   │ 148           │ 0.00018  │
│ ERR6913196    │ Human betaherpesvirus 6B │ 134           │ 0.00017  │
│ ERR6913327    │ Human mastadenovirus C   │ 63            │ 0.00014  │
│ ERR6913189    │ Bacteroides humanifaecis │ 79            │ 0.00012  │
│ ERR6913202    │ Human gammaherpesvirus 4 │ 71            │ 0.00012  │
│ ERR6913282    │ Human mastadenovirus C   │ 112           │ 0.0001   │
│ ERR6913205    │ Human betaherpesvirus 6B │ 39            │ 0.0001   │
│ ERR6913194    │ Bacteroides humanifaecis │ 49            │ 9.0e-05  │
│ ERR6913283    │ Human mastadenovirus C   │ 8             │ 7.0e-05  │
│ ERR6913335    │ Human gammaherpesvirus 4 │ 42            │ 6.0e-05  │
│ ERR6913283    │ Human betaherpesvirus 7  │ 6             │ 5.0e-05  │
│ ERR6913196    │ Bacteroides humanifaecis │ 41            │ 5.0e-05  │
│ ERR6913101    │ Human gammaherpesvirus 4 │ 5             │ 4.0e-05  │
│ ERR6913197    │ Human mastadenovirus C   │ 8             │ 4.0e-05  │
│ ERR6913230    │ Human mastadenovirus C   │ 10            │ 4.0e-05  │
│ ERR6913197    │ Human gammaherpesvirus 4 │ 6             │ 3.0e-05  │
│ ERR6913275    │ Human mastadenovirus C   │ 8             │ 3.0e-05  │
│ ERR6913277    │ Human mastadenovirus C   │ 33            │ 3.0e-05  │
│ ERR6913271    │ Human mastadenovirus C   │ 16            │ 3.0e-05  │
│ ERR6913232    │ Human mastadenovirus C   │ 38            │ 3.0e-05  │
│ ERR6913138    │ Human gammaherpesvirus 4 │ 21            │ 3.0e-05  │
│ ERR6913333    │ Human mastadenovirus C   │ 23            │ 3.0e-05  │
│ ERR6913139    │ Human gammaherpesvirus 4 │ 21            │ 3.0e-05  │
│ ERR6913233    │ Human mastadenovirus C   │ 50            │ 3.0e-05  │
│ ERR6913129    │ Human betaherpesvirus 7  │ 5             │ 3.0e-05  │
│ ERR6913287    │ Human mastadenovirus C   │ 18            │ 2.0e-05  │
│ ERR6913281    │ Human mastadenovirus C   │ 23            │ 2.0e-05  │
│ ERR6913345    │ Human mastadenovirus C   │ 21            │ 2.0e-05  │
│ ERR6913225    │ Human mastadenovirus C   │ 29            │ 2.0e-05  │
│ ERR6913349    │ Human mastadenovirus C   │ 14            │ 1.0e-05  │
│ ERR6913285    │ Human mastadenovirus C   │ 10            │ 1.0e-05  │
│ ERR6913326    │ Human mastadenovirus C   │ 12            │ 1.0e-05  │
│ ERR6913183    │ Human gammaherpesvirus 4 │ 5             │ 1.0e-05  │
│ ERR6913305    │ Human betaherpesvirus 7  │ 8             │ 1.0e-05  │
│ ERR6913341    │ Human gammaherpesvirus 4 │ 5             │ 1.0e-05  │
│ ERR6913341    │ Human mastadenovirus C   │ 5             │ 1.0e-05  │
│ ERR6913200    │ Human mastadenovirus C   │ 6             │ 1.0e-05  │
│ ERR6913228    │ Human mastadenovirus C   │ 9             │ 1.0e-05  │
│ ERR6913231    │ Human mastadenovirus C   │ 15            │ 1.0e-05  │
│ ERR6913226    │ Human mastadenovirus C   │ 17            │ 1.0e-05  │
│ ERR6913292    │ Human betaherpesvirus 6B │ 12            │ 1.0e-05  │
│ ERR6913234    │ Human mastadenovirus C   │ 6             │ 0.0      │
│ ERR6913130    │ Human betaherpesvirus 7  │ 1             │ 0.0      │
│ ERR6913196    │ Human betaherpesvirus 7  │ 1             │ 0.0      │
│ ERR6913292    │ Human mastadenovirus C   │ 2             │ 0.0      │
└───────────────┴──────────────────────────┴───────────────┴──────────┘

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT * FROM CtValues LIMIT 2;'

Blinded_number  Ct 
--------------  ---
P105            0.0
P113            0.0

sqlite3 -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT * FROM sample_annot LIMIT 2;'

run_accession  host_subject_id    patient_code  nuc  host_body_site  host_disease_status  miscellaneous_parameter    Ct     total_reads  read_count  base_count
-------------  -----------------  ------------  ---  --------------  -------------------  -------------------------  -----  -----------  ----------  ----------
ERR6913102     P011_DNA_S39_L001  P11           DNA  Nasopharyngeal  SARS-CoV-2 positive  Symptomatic-DNA-sequenced  23.59  27630988     102524      13193813  
ERR6913103     P019_DNA_S74_L001  P19           DNA  Nasopharyngeal  SARS-CoV-2 positive  Symptomatic-DNA-sequenced  18.81  21364260     385740      49060845  

sqlite3 -box -batch /shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db \
'SELECT run_accession,taxon_name,new_est_reads AS reads,fraction_total_reads AS fraction, nuc, host_disease_status, total_reads, read_count, Ct
 FROM bracken_abundances_long abu LEFT JOIN sample_annot spl using (run_accession)
 WHERE taxon_name LIKE "%corona%"
 ORDER BY fraction_total_reads DESC;'

┌───────────────┬───────────────────────────────────────────────────────┬───────┬──────────┬─────┬─────────────────────┬─────────────┬────────────┬───────┐
│ run_accession │                      taxon_name                       │ reads │ fraction │ nuc │ host_disease_status │ total_reads │ read_count │  Ct   │
├───────────────┼───────────────────────────────────────────────────────┼───────┼──────────┼─────┼─────────────────────┼─────────────┼────────────┼───────┤
│ ERR6913216    │ Severe acute respiratory syndrome-related coronavirus │ 7797  │ 0.77822  │ RNA │ SARS-CoV-2 positive │ 17198782    │ 39552      │ 17.99 │
│ ERR6913199    │ Severe acute respiratory syndrome-related coronavirus │ 439   │ 0.7569   │ RNA │ SARS-CoV-2 positive │ 20758064    │ 62396      │ 18.81 │
│ ERR6913221    │ Severe acute respiratory syndrome-related coronavirus │ 4360  │ 0.73823  │ RNA │ SARS-CoV-2 positive │ 19171612    │ 23570      │ 17.88 │
│ ERR6913210    │ Severe acute respiratory syndrome-related coronavirus │ 6142  │ 0.41324  │ RNA │ SARS-CoV-2 positive │ 21965834    │ 107788     │ 19.52 │
│ ERR6913214    │ Severe acute respiratory syndrome-related coronavirus │ 4573  │ 0.38784  │ RNA │ SARS-CoV-2 positive │ 21508942    │ 79318      │ 17.81 │
│ ERR6913211    │ Severe acute respiratory syndrome-related coronavirus │ 150   │ 0.28791  │ RNA │ SARS-CoV-2 positive │ 17691576    │ 39562      │ 19.63 │
│ ERR6913215    │ Severe acute respiratory syndrome-related coronavirus │ 2365  │ 0.22142  │ RNA │ SARS-CoV-2 positive │ 17125668    │ 84944      │ 18.89 │
│ ERR6913203    │ Severe acute respiratory syndrome-related coronavirus │ 1318  │ 0.2193   │ RNA │ SARS-CoV-2 positive │ 22052590    │ 31944      │ 19.38 │
│ ERR6913217    │ Severe acute respiratory syndrome-related coronavirus │ 5938  │ 0.19576  │ RNA │ SARS-CoV-2 positive │ 20352976    │ 203098     │ 17.56 │
│ ERR6913204    │ Severe acute respiratory syndrome-related coronavirus │ 2468  │ 0.17501  │ RNA │ SARS-CoV-2 positive │ 27571556    │ 47600      │ 18.42 │
│ ERR6913219    │ Severe acute respiratory syndrome-related coronavirus │ 11656 │ 0.04292  │ RNA │ SARS-CoV-2 positive │ 18437710    │ 615136     │ 17.93 │
│ ERR6913213    │ Severe acute respiratory syndrome-related coronavirus │ 10    │ 0.04115  │ RNA │ SARS-CoV-2 positive │ 26128248    │ 31868      │ 21.34 │
│ ERR6913197    │ Severe acute respiratory syndrome-related coronavirus │ 8980  │ 0.04034  │ RNA │ SARS-CoV-2 positive │ 27027782    │ 758080     │ 18.0  │
│ ERR6913212    │ Severe acute respiratory syndrome-related coronavirus │ 23    │ 0.03651  │ RNA │ SARS-CoV-2 positive │ 20644176    │ 6948       │ 23.43 │
│ ERR6913261    │ Human coronavirus NL63                                │ 21    │ 0.02909  │ RNA │ SARS-CoV-2 negative │ 24026306    │ 8410       │ 0.0   │
│ ERR6913208    │ Severe acute respiratory syndrome-related coronavirus │ 968   │ 0.02116  │ RNA │ SARS-CoV-2 positive │ 17354398    │ 109226     │ 19.95 │
│ ERR6913220    │ Severe acute respiratory syndrome-related coronavirus │ 736   │ 0.01979  │ RNA │ SARS-CoV-2 positive │ 18372966    │ 85976      │ 19.64 │
│ ERR6913218    │ Severe acute respiratory syndrome-related coronavirus │ 1532  │ 0.0171   │ RNA │ SARS-CoV-2 positive │ 21843848    │ 286382     │ 17.55 │
│ ERR6913252    │ Human coronavirus HKU1                                │ 80    │ 0.01059  │ RNA │ SARS-CoV-2 negative │ 22690768    │ 19934      │ 0.0   │
│ ERR6913121    │ Severe acute respiratory syndrome-related coronavirus │ 77    │ 0.00777  │ DNA │ SARS-CoV-2 positive │ 19030318    │ 120658     │ 17.56 │
│ ERR6913209    │ Severe acute respiratory syndrome-related coronavirus │ 24    │ 0.00753  │ RNA │ SARS-CoV-2 positive │ 28082388    │ 28014      │ 23.92 │
│ ERR6913200    │ Severe acute respiratory syndrome-related coronavirus │ 4760  │ 0.00751  │ RNA │ SARS-CoV-2 positive │ 19148958    │ 1392334    │ 18.02 │
│ ERR6913327    │ Severe acute respiratory syndrome-related coronavirus │ 1484  │ 0.0032   │ RNA │ SARS-CoV-2 positive │ 12183696    │ 1119746    │ 23.37 │
│ ERR6913267    │ Severe acute respiratory syndrome-related coronavirus │ 12    │ 0.00242  │ RNA │ SARS-CoV-2 negative │ 21777586    │ 84794      │ 0.0   │
│ ERR6913254    │ Severe acute respiratory syndrome-related coronavirus │ 17    │ 0.00226  │ RNA │ SARS-CoV-2 negative │ 7605936     │ 99900      │ 0.0   │
│ ERR6913268    │ Severe acute respiratory syndrome-related coronavirus │ 64    │ 0.0014   │ RNA │ SARS-CoV-2 negative │ 18099096    │ 354056     │ 0.0   │
│ ERR6913126    │ Severe acute respiratory syndrome-related coronavirus │ 76    │ 0.00136  │ DNA │ SARS-CoV-2 positive │ 20908814    │ 731096     │ 17.28 │
│ ERR6913101    │ Severe acute respiratory syndrome-related coronavirus │ 128   │ 0.00106  │ DNA │ SARS-CoV-2 positive │ 20246544    │ 658268     │ 18.0  │
│ ERR6913326    │ Severe acute respiratory syndrome-related coronavirus │ 828   │ 0.00092  │ RNA │ SARS-CoV-2 positive │ 25509490    │ 2349534    │ 20.29 │
│ ERR6913328    │ Severe acute respiratory syndrome-related coronavirus │ 104   │ 0.00069  │ RNA │ SARS-CoV-2 positive │ 23559354    │ 1115208    │ 25.72 │
│ ERR6913275    │ Severe acute respiratory syndrome-related coronavirus │ 168   │ 0.00063  │ RNA │ SARS-CoV-2 negative │ 20429462    │ 606162     │ 27.65 │
│ ERR6913122    │ Severe acute respiratory syndrome-related coronavirus │ 92    │ 0.00053  │ DNA │ SARS-CoV-2 positive │ 19148784    │ 745326     │ 17.55 │
│ ERR6913315    │ Severe acute respiratory syndrome-related coronavirus │ 84    │ 0.00053  │ DNA │ SARS-CoV-2 negative │ 21468280    │ 746902     │ 0.0   │
│ ERR6913331    │ Severe acute respiratory syndrome-related coronavirus │ 100   │ 0.00047  │ RNA │ SARS-CoV-2 positive │ 23702012    │ 846014     │ 25.49 │
│ ERR6913305    │ Severe acute respiratory syndrome-related coronavirus │ 298   │ 0.00046  │ DNA │ SARS-CoV-2 negative │ 27251714    │ 1874096    │ 0.0   │
│ ERR6913293    │ Severe acute respiratory syndrome-related coronavirus │ 79    │ 0.00044  │ DNA │ SARS-CoV-2 positive │ 18338068    │ 823494     │ 17.53 │
│ ERR6913322    │ Severe acute respiratory syndrome-related coronavirus │ 517   │ 0.00044  │ RNA │ SARS-CoV-2 positive │ 11522192    │ 2441696    │ 17.53 │
│ ERR6913226    │ Severe acute respiratory syndrome-related coronavirus │ 428   │ 0.00035  │ RNA │ SARS-CoV-2 positive │ 18028410    │ 2732518    │       │
│ ERR6913230    │ Severe acute respiratory syndrome-related coronavirus │ 76    │ 0.00032  │ RNA │ SARS-CoV-2 positive │ 15306918    │ 626228     │ 23.01 │
│ ERR6913233    │ Severe acute respiratory syndrome-related coronavirus │ 444   │ 0.0003   │ RNA │ SARS-CoV-2 positive │ 12640954    │ 3469648    │ 26.37 │
│ ERR6913205    │ Severe acute respiratory syndrome-related coronavirus │ 87    │ 0.00023  │ RNA │ SARS-CoV-2 positive │ 21029778    │ 805170     │ 23.66 │
│ ERR6913312    │ Severe acute respiratory syndrome-related coronavirus │ 39    │ 0.0002   │ DNA │ SARS-CoV-2 negative │ 18705528    │ 1001132    │ 0.0   │
│ ERR6913295    │ Severe acute respiratory syndrome-related coronavirus │ 5     │ 0.00019  │ DNA │ SARS-CoV-2 positive │ 1449648     │ 203638     │ 25.64 │
│ ERR6913324    │ Severe acute respiratory syndrome-related coronavirus │ 5     │ 0.00019  │ RNA │ SARS-CoV-2 positive │ 1449648     │ 203638     │ 25.64 │
│ ERR6913104    │ Severe acute respiratory syndrome-related coronavirus │ 29    │ 0.00017  │ DNA │ SARS-CoV-2 positive │ 22910206    │ 610606     │ 18.02 │
│ ERR6913334    │ Severe acute respiratory syndrome-related coronavirus │ 101   │ 0.00013  │ RNA │ SARS-CoV-2 negative │ 20238122    │ 1736934    │ 0.0   │
│ ERR6913202    │ Severe acute respiratory syndrome-related coronavirus │ 55    │ 9.0e-05  │ RNA │ SARS-CoV-2 positive │ 21061776    │ 1416556    │ 19.59 │
│ ERR6913242    │ Severe acute respiratory syndrome-related coronavirus │ 50    │ 7.0e-05  │ RNA │ SARS-CoV-2 positive │ 24149962    │ 2583114    │       │
│ ERR6913333    │ Severe acute respiratory syndrome-related coronavirus │ 43    │ 5.0e-05  │ RNA │ SARS-CoV-2 positive │ 17030332    │ 1962584    │ 23.52 │
│ ERR6913276    │ Severe acute respiratory syndrome-related coronavirus │ 26    │ 3.0e-05  │ RNA │ SARS-CoV-2 negative │ 17780890    │ 3177948    │ 21.94 │
│ ERR6913276    │ Pseudomonas coronafaciens                             │ 21    │ 2.0e-05  │ RNA │ SARS-CoV-2 negative │ 17780890    │ 3177948    │ 21.94 │
│ ERR6913222    │ Severe acute respiratory syndrome-related coronavirus │ 13    │ 2.0e-05  │ RNA │ SARS-CoV-2 positive │ 24783540    │ 1834540    │ 17.28 │
│ ERR6913306    │ Severe acute respiratory syndrome-related coronavirus │ 6     │ 2.0e-05  │ DNA │ SARS-CoV-2 negative │ 18684426    │ 744842     │ 0.0   │
│ ERR6913345    │ Severe acute respiratory syndrome-related coronavirus │ 26    │ 2.0e-05  │ RNA │ SARS-CoV-2 negative │ 21714858    │ 2750394    │ 0.0   │
│ ERR6913325    │ Severe acute respiratory syndrome-related coronavirus │ 10    │ 2.0e-05  │ RNA │ SARS-CoV-2 positive │ 19664100    │ 1824222    │ 24.14 │
│ ERR6913313    │ Severe acute respiratory syndrome-related coronavirus │ 13    │ 2.0e-05  │ DNA │ SARS-CoV-2 negative │ 14895168    │ 2136132    │ 0.0   │
│ ERR6913342    │ Severe acute respiratory syndrome-related coronavirus │ 34    │ 2.0e-05  │ RNA │ SARS-CoV-2 negative │ 17613434    │ 3754758    │ 0.0   │
│ ERR6913323    │ Severe acute respiratory syndrome-related coronavirus │ 20    │ 2.0e-05  │ RNA │ SARS-CoV-2 positive │ 19424544    │ 3066570    │ 22.39 │
│ ERR6913271    │ Severe acute respiratory syndrome-related coronavirus │ 6     │ 1.0e-05  │ RNA │ SARS-CoV-2 negative │ 23805264    │ 1309086    │       │
│ ERR6913307    │ Severe acute respiratory syndrome-related coronavirus │ 5     │ 1.0e-05  │ DNA │ SARS-CoV-2 negative │ 20818628    │ 1250426    │ 0.0   │
│ ERR6913343    │ Severe acute respiratory syndrome-related coronavirus │ 11    │ 1.0e-05  │ RNA │ SARS-CoV-2 negative │ 41696524    │ 3478632    │ 0.0   │
│ ERR6913228    │ Severe acute respiratory syndrome-related coronavirus │ 5     │ 1.0e-05  │ RNA │ SARS-CoV-2 positive │ 21482936    │ 2298768    │ 25.21 │
│ ERR6913196    │ Pseudomonas coronafaciens                             │ 7     │ 1.0e-05  │ DNA │ SARS-CoV-2 negative │ 22682382    │ 2236474    │ 18.29 │
│ ERR6913344    │ Severe acute respiratory syndrome-related coronavirus │ 5     │ 0.0      │ RNA │ SARS-CoV-2 negative │ 22834560    │ 2380636    │ 0.0   │
│ ERR6913194    │ Pseudomonas coronafaciens                             │ 2     │ 0.0      │ DNA │ SARS-CoV-2 negative │ 18826866    │ 1386316    │ 27.0  │
│ ERR6913225    │ Severe acute respiratory syndrome-related coronavirus │ 1     │ 0.0      │ RNA │ SARS-CoV-2 positive │ 26601948    │ 2727870    │ 22.55 │
│ ERR6913290    │ Severe acute respiratory syndrome-related coronavirus │ 2     │ 0.0      │ RNA │ SARS-CoV-2 negative │ 22660356    │ 2558148    │ 27.0  │
│ ERR6913292    │ Severe acute respiratory syndrome-related coronavirus │ 2     │ 0.0      │ RNA │ SARS-CoV-2 negative │ 21276022    │ 2702312    │ 18.29 │
└───────────────┴───────────────────────────────────────────────────────┴───────┴──────────┴─────┴─────────────────────┴─────────────┴────────────┴───────┘

DAY5

Build "long" and "wide" versions of the abundance matrix in R

R session

library(DBI)
library(tidyverse)

Warning message in system("timedatectl", intern = TRUE):
“running command 'timedatectl' had status 1”
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

✔ ggplot2 3.3.5     ✔ purrr   0.3.4
✔ tibble  3.1.8     ✔ dplyr   1.0.7
✔ tidyr   1.1.4     ✔ stringr 1.4.0
✔ readr   2.1.0     ✔ forcats 0.5.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

"long" version

mydb <- dbConnect(RSQLite::SQLite(), "/shared/projects/2314_medbioinfo/pascal/central_database/sample_collab.db")

options(tibble.width=200, tibble.print_max = 200, tibble.print_min = 5, width = 280, max.print=200,pillar.bold=TRUE, pillar.subtle=0, pillar.min_title_chars=7, pillar.sigfig=1)

abun_long <- as_tibble(dbGetQuery(mydb, "select * from bracken_abundances_long abu left join sample_annot spl using(run_accession);"))

abun_long

A tibble: 144718 × 18

run_accession	taxon_name	taxonomy_id	taxonomy_lvl	kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads	host_subject_id	patient_code	nuc	host_body_site	host_disease_status	miscellaneous_parameter	Ct	total_reads	read_count	base_count
<chr>	<chr>	<int>	<chr>	<int>	<int>	<int>	<dbl>	<chr>	<chr>	<chr>	<chr>	<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913112	Streptococcus oralis	1303	S	315	139	454	0.04101	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus sp. LPB0220	2610896	S	64	14	78	0.00705	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus sp. HSISM1	1316408	S	50	10	60	0.00542	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus sp. oral taxon 064	712624	S	14	21	35	0.00316	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus sp. oral taxon 061	712623	S	11	1	12	0.00108	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus salivarius	1304	S	171	60	231	0.02087	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus mitis	28037	S	135	24	159	0.01436	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus intermedius	1338	S	106	32	138	0.01246	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus vestibularis	1343	S	69	10	79	0.00714	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus parasanguinis	1318	S	59	9	68	0.00614	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus gordonii	1302	S	57	2	59	0.00533	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus pneumoniae	1313	S	25	17	42	0.00379	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus mutans	1309	S	24	1	25	0.00226	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus infantis	68892	S	21	2	23	0.00208	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus gwangjuense	1433513	S	17	5	22	0.00199	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Streptococcus pseudopneumoniae	257758	S	11	3	14	0.00126	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Dolosigranulum pigrum	29394	S	514	4	518	0.04679	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Granulicatella adiacens	46124	S	21	0	21	0.00190	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Ligilactobacillus salivarius	1624	S	103	10	113	0.01021	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Limosilactobacillus portuensis	2742601	S	48	9	57	0.00515	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Limosilactobacillus fermentum	1613	S	11	3	14	0.00126	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Lactobacillus gasseri	1596	S	24	9	33	0.00298	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Lactobacillus crispatus	47770	S	13	0	13	0.00117	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Enterococcus cecorum	44008	S	47	1	48	0.00434	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Staphylococcus epidermidis	1282	S	33	13	46	0.00415	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Veillonella parvula	29466	S	240	5	245	0.02213	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Veillonella atypica	39777	S	112	2	114	0.01030	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Veillonella nakazawae	2682456	S	112	33	145	0.01310	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Veillonella dispar	39778	S	78	10	88	0.00795	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
ERR6913112	Veillonella sp. S12025-13	2682455	S	65	15	80	0.00723	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
ERR6913223	Pseudomonas fluorescens	294	S	17	96	113	0.00020	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Haemophilus parainfluenzae	729	S	60	96	156	0.00028	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Xanthomonas campestris	339	S	25	98	123	0.00022	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Stenotrophomonas maltophilia	40324	S	18	24	42	0.00007	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Cardiobacterium hominis	2718	S	16	8	24	0.00004	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Cardiobacterium sp. Marseille-Q4385	2866573	S	11	4	15	0.00003	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Lautropia mirabilis	47671	S	79	86	165	0.00029	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Achromobacter deleyi	1353891	S	13	27	40	0.00007	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Dechloromonas sp. A34	447588	S	30	11	41	0.00007	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Dechloromonas sp. TW-R-39-2	2654218	S	10	10	20	0.00004	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Dechloromonas denitrificans	281362	S	33	16	49	0.00009	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Ferribacterium limneticum	76259	S	78	28	106	0.00019	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Quatrionicoccus australiensis	138118	S	26	17	43	0.00008	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Azospira oryzae	146939	S	11	35	46	0.00008	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Kingella oralis	505	S	11	149	160	0.00028	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Mesorhizobium terrae	2725666	S	25	54	79	0.00014	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Methylobacterium sp. FF17	2984843	S	16	9	25	0.00004	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Novosphingobium sp. EMRT-2	2571749	S	26	44	70	0.00012	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Prevotella sp. oral taxon 475	712471	S	23	16	39	0.00007	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Prevotella sp. oral taxon 299	652716	S	17	26	43	0.00008	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Porphyromonas sp. oral taxon 275	712435	S	29	14	43	0.00008	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Capnocytophaga gingivalis	1017	S	35	20	55	0.00010	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Capnocytophaga sputigena	1019	S	32	52	84	0.00015	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Fusobacterium nucleatum	851	S	24	126	150	0.00026	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Leptotrichia sp. oral taxon 212	712357	S	104	18	122	0.00022	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Phaeodactylum tricornutum	2850	S	137	8	145	0.00026	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Thalassiosira pseudonana	35128	S	101	10	111	0.00020	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Homo sapiens	9606	S	130	41	171	0.00030	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Malassezia restricta	76775	S	27	7	34	0.00006	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396
ERR6913223	Severe acute respiratory syndrome-related coronavirus	694009	S	105	0	105	0.00019	P381_cDNA_L001	P381	RNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-cDNA-sequenced	22.18	21573718	1173894	158775396

slice_head(abun_long)

A tibble: 1 × 18

run_accession	taxon_name	taxonomy_id	taxonomy_lvl	kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads	host_subject_id	patient_code	nuc	host_body_site	host_disease_status	miscellaneous_parameter	Ct	total_reads	read_count	base_count
<chr>	<chr>	<int>	<chr>	<int>	<int>	<int>	<dbl>	<chr>	<chr>	<chr>	<chr>	<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913112	Streptococcus oralis	1303	S	315	139	454	0.04101	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624

abun_long %>% select(kraken_assigned_reads,added_reads,new_est_reads,fraction_total_reads)

A tibble: 144718 × 4

kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads
<int>	<int>	<int>	<dbl>
315	139	454	0.04101
64	14	78	0.00705
50	10	60	0.00542
14	21	35	0.00316
11	1	12	0.00108
171	60	231	0.02087
135	24	159	0.01436
106	32	138	0.01246
69	10	79	0.00714
59	9	68	0.00614
57	2	59	0.00533
25	17	42	0.00379
24	1	25	0.00226
21	2	23	0.00208
17	5	22	0.00199
11	3	14	0.00126
514	4	518	0.04679
21	0	21	0.00190
103	10	113	0.01021
48	9	57	0.00515
11	3	14	0.00126
24	9	33	0.00298
13	0	13	0.00117
47	1	48	0.00434
33	13	46	0.00415
240	5	245	0.02213
112	2	114	0.01030
112	33	145	0.01310
78	10	88	0.00795
65	15	80	0.00723
⋮	⋮	⋮	⋮
17	96	113	0.00020
60	96	156	0.00028
25	98	123	0.00022
18	24	42	0.00007
16	8	24	0.00004
11	4	15	0.00003
79	86	165	0.00029
13	27	40	0.00007
30	11	41	0.00007
10	10	20	0.00004
33	16	49	0.00009
78	28	106	0.00019
26	17	43	0.00008
11	35	46	0.00008
11	149	160	0.00028
25	54	79	0.00014
16	9	25	0.00004
26	44	70	0.00012
23	16	39	0.00007
17	26	43	0.00008
29	14	43	0.00008
35	20	55	0.00010
32	52	84	0.00015
24	126	150	0.00026
104	18	122	0.00022
137	8	145	0.00026
101	10	111	0.00020
130	41	171	0.00030
27	7	34	0.00006
105	0	105	0.00019

dim(abun_long)

1. 144718
2. 18

summary(abun_long$fraction_total_reads)

    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
0.000000 0.000010 0.000030 0.001365 0.000160 1.000000 

abun_long %>% 
  select(run_accession, taxon_name, fraction_total_reads, new_est_reads, read_count, total_reads)

A tibble: 144718 × 6

run_accession	taxon_name	fraction_total_reads	new_est_reads	read_count	total_reads
<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913112	Streptococcus oralis	0.04101	454	63444	25543682
ERR6913112	Streptococcus sp. LPB0220	0.00705	78	63444	25543682
ERR6913112	Streptococcus sp. HSISM1	0.00542	60	63444	25543682
ERR6913112	Streptococcus sp. oral taxon 064	0.00316	35	63444	25543682
ERR6913112	Streptococcus sp. oral taxon 061	0.00108	12	63444	25543682
ERR6913112	Streptococcus salivarius	0.02087	231	63444	25543682
ERR6913112	Streptococcus mitis	0.01436	159	63444	25543682
ERR6913112	Streptococcus intermedius	0.01246	138	63444	25543682
ERR6913112	Streptococcus vestibularis	0.00714	79	63444	25543682
ERR6913112	Streptococcus parasanguinis	0.00614	68	63444	25543682
ERR6913112	Streptococcus gordonii	0.00533	59	63444	25543682
ERR6913112	Streptococcus pneumoniae	0.00379	42	63444	25543682
ERR6913112	Streptococcus mutans	0.00226	25	63444	25543682
ERR6913112	Streptococcus infantis	0.00208	23	63444	25543682
ERR6913112	Streptococcus gwangjuense	0.00199	22	63444	25543682
ERR6913112	Streptococcus pseudopneumoniae	0.00126	14	63444	25543682
ERR6913112	Dolosigranulum pigrum	0.04679	518	63444	25543682
ERR6913112	Granulicatella adiacens	0.00190	21	63444	25543682
ERR6913112	Ligilactobacillus salivarius	0.01021	113	63444	25543682
ERR6913112	Limosilactobacillus portuensis	0.00515	57	63444	25543682
ERR6913112	Limosilactobacillus fermentum	0.00126	14	63444	25543682
ERR6913112	Lactobacillus gasseri	0.00298	33	63444	25543682
ERR6913112	Lactobacillus crispatus	0.00117	13	63444	25543682
ERR6913112	Enterococcus cecorum	0.00434	48	63444	25543682
ERR6913112	Staphylococcus epidermidis	0.00415	46	63444	25543682
ERR6913112	Veillonella parvula	0.02213	245	63444	25543682
ERR6913112	Veillonella atypica	0.01030	114	63444	25543682
ERR6913112	Veillonella nakazawae	0.01310	145	63444	25543682
ERR6913112	Veillonella dispar	0.00795	88	63444	25543682
ERR6913112	Veillonella sp. S12025-13	0.00723	80	63444	25543682
⋮	⋮	⋮	⋮	⋮	⋮
ERR6913223	Pseudomonas fluorescens	0.00020	113	1173894	21573718
ERR6913223	Haemophilus parainfluenzae	0.00028	156	1173894	21573718
ERR6913223	Xanthomonas campestris	0.00022	123	1173894	21573718
ERR6913223	Stenotrophomonas maltophilia	0.00007	42	1173894	21573718
ERR6913223	Cardiobacterium hominis	0.00004	24	1173894	21573718
ERR6913223	Cardiobacterium sp. Marseille-Q4385	0.00003	15	1173894	21573718
ERR6913223	Lautropia mirabilis	0.00029	165	1173894	21573718
ERR6913223	Achromobacter deleyi	0.00007	40	1173894	21573718
ERR6913223	Dechloromonas sp. A34	0.00007	41	1173894	21573718
ERR6913223	Dechloromonas sp. TW-R-39-2	0.00004	20	1173894	21573718
ERR6913223	Dechloromonas denitrificans	0.00009	49	1173894	21573718
ERR6913223	Ferribacterium limneticum	0.00019	106	1173894	21573718
ERR6913223	Quatrionicoccus australiensis	0.00008	43	1173894	21573718
ERR6913223	Azospira oryzae	0.00008	46	1173894	21573718
ERR6913223	Kingella oralis	0.00028	160	1173894	21573718
ERR6913223	Mesorhizobium terrae	0.00014	79	1173894	21573718
ERR6913223	Methylobacterium sp. FF17	0.00004	25	1173894	21573718
ERR6913223	Novosphingobium sp. EMRT-2	0.00012	70	1173894	21573718
ERR6913223	Prevotella sp. oral taxon 475	0.00007	39	1173894	21573718
ERR6913223	Prevotella sp. oral taxon 299	0.00008	43	1173894	21573718
ERR6913223	Porphyromonas sp. oral taxon 275	0.00008	43	1173894	21573718
ERR6913223	Capnocytophaga gingivalis	0.00010	55	1173894	21573718
ERR6913223	Capnocytophaga sputigena	0.00015	84	1173894	21573718
ERR6913223	Fusobacterium nucleatum	0.00026	150	1173894	21573718
ERR6913223	Leptotrichia sp. oral taxon 212	0.00022	122	1173894	21573718
ERR6913223	Phaeodactylum tricornutum	0.00026	145	1173894	21573718
ERR6913223	Thalassiosira pseudonana	0.00020	111	1173894	21573718
ERR6913223	Homo sapiens	0.00030	171	1173894	21573718
ERR6913223	Malassezia restricta	0.00006	34	1173894	21573718
ERR6913223	Severe acute respiratory syndrome-related coronavirus	0.00019	105	1173894	21573718

abun_long %>% 
 select(run_accession, taxon_name, fraction_total_reads, new_est_reads, read_count, total_reads) %>% 
 filter(fraction_total_reads>0.1)

A tibble: 291 × 6

run_accession	taxon_name	fraction_total_reads	new_est_reads	read_count	total_reads
<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913112	Moraxella nonliquefaciens	0.30232	3347	63444	25543682
ERR6913113	Vibrio kanaloae	0.17019	1803	223844	21821962
ERR6913320	Prevotella melaninogenica	0.24837	129907	1873994	22695514
ERR6913209	Corynebacterium segmentosum	0.14747	470	28014	28082388
ERR6913209	Corynebacterium accolens	0.12112	386	28014	28082388
ERR6913209	Acinetobacter junii	0.18826	600	28014	28082388
ERR6913122	Prevotella jejuni	0.16345	28510	745326	19148784
ERR6913208	Moraxella nonliquefaciens	0.43645	19969	109226	17354398
ERR6913208	Moraxella bovoculi	0.14709	6730	109226	17354398
ERR6913218	Prevotella jejuni	0.15228	13646	286382	21843848
ERR6913349	Prevotella melaninogenica	0.30589	460396	3193196	45144918
ERR6913179	Prevotella melaninogenica	0.17401	115656	1769196	17377298
ERR6913180	Prevotella melaninogenica	0.15419	105412	2234368	22081900
ERR6913181	Streptococcus salivarius	0.47683	461431	2252564	19977940
ERR6913181	Veillonella atypica	0.15035	145490	2252564	19977940
ERR6913276	Cutibacterium acnes	0.42643	387713	3177948	17780890
ERR6913278	Veillonella parvula	0.10595	134990	2714728	20047904
ERR6913278	Neisseria mucosa	0.13850	176462	2714728	20047904
ERR6913101	Klebsiella pneumoniae	0.33502	40475	658268	20246544
ERR6913197	Klebsiella pneumoniae	0.32262	71821	758080	27027782
ERR6913275	Streptococcus mitis	0.12788	34155	606162	20429462
ERR6913275	Streptococcus pneumoniae	0.34980	93424	606162	20429462
ERR6913277	Streptococcus salivarius	0.27982	344828	2870764	25512276
ERR6913277	Veillonella atypica	0.12616	155472	2870764	25512276
ERR6913191	Prevotella intermedia	0.29980	27960	283316	19546192
ERR6913193	Streptococcus salivarius	0.11692	39960	812494	21176470
ERR6913193	Rothia mucilaginosa	0.10168	34753	812494	21176470
ERR6913236	Prevotella veroralis	0.10667	152080	3303920	15718784
ERR6913291	Veillonella atypica	0.14908	179292	2739370	26470190
ERR6913291	Veillonella parvula	0.10593	127399	2739370	26470190
⋮	⋮	⋮	⋮	⋮	⋮
ERR6913266	Streptococcus sanguinis	0.10005	189	9030	22310726
ERR6913266	Veillonella parvula	0.12546	237	9030	22310726
ERR6913266	Cutibacterium acnes	0.16040	303	9030	22310726
ERR6913109	Cutibacterium acnes	0.12969	1050	59176	24507262
ERR6913164	Vibrio kanaloae	0.22370	1140	231186	21971474
ERR6913164	Pseudoalteromonas prydzensis	0.13108	668	231186	21971474
ERR6913172	Vibrio kanaloae	0.18087	9900	1047306	22377066
ERR6913260	Cutibacterium acnes	0.20569	340	27568	20149704
ERR6913260	Pasteurella multocida	0.10829	179	27568	20149704
ERR6913260	Phaeodactylum tricornutum	0.10284	170	27568	20149704
ERR6913129	Streptococcus salivarius	0.11233	20655	471008	19556696
ERR6913129	Porphyromonas endodontalis	0.11378	20923	471008	19556696
ERR6913130	Prevotella jejuni	0.21377	51425	649836	21999026
ERR6913194	Streptococcus salivarius	0.10752	56663	1386316	18826866
ERR6913196	Prevotella melaninogenica	0.25634	207296	2236474	22682382
ERR6913196	Veillonella atypica	0.10632	85977	2236474	22682382
ERR6913225	Streptococcus salivarius	0.11755	136996	2727870	26601948
ERR6913226	Streptococcus agalactiae	0.11158	134816	2732518	18028410
ERR6913292	Prevotella melaninogenica	0.25416	318340	2702312	21276022
ERR6913292	Veillonella atypica	0.10924	136830	2702312	21276022
ERR6913300	Veillonella atypica	0.17056	75246	1700124	20679390
ERR6913300	Prevotella melaninogenica	0.12738	56198	1700124	20679390
ERR6913301	Prevotella jejuni	0.16039	38567	907928	28012624
ERR6913303	Staphylococcus aureus	0.62618	597928	2139748	20103510
ERR6913332	Staphylococcus aureus	0.61502	684696	2489352	24091268
ERR6913127	Dolosigranulum pigrum	0.48795	2652	30170	19048514
ERR6913127	Corynebacterium pseudodiphtheriticum	0.30175	1640	30170	19048514
ERR6913223	Corynebacterium pseudodiphtheriticum	0.30164	170981	1173894	21573718
ERR6913223	Corynebacterium glutamicum	0.11430	64790	1173894	21573718
ERR6913223	Dolosigranulum pigrum	0.46865	265649	1173894	21573718

abun_long %>%
 select(run_accession, taxon_name, fraction_total_reads, new_est_reads, read_count, total_reads) %>%
 filter(fraction_total_reads>0.1) %>%
 arrange(desc(fraction_total_reads))

A tibble: 291 × 6

run_accession	taxon_name	fraction_total_reads	new_est_reads	read_count	total_reads
<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913115	Cutibacterium acnes	1.00000	79	33254	18306476
ERR6913154	Haemophilus influenzae	0.98190	15187	39244	18749066
ERR6913269	Influenza A virus	0.97180	11614	25426	23544470
ERR6913264	Haemophilus influenzae	0.92120	4618	21382	18079420
ERR6913250	Haemophilus influenzae	0.88349	73565	169548	18898684
ERR6913252	Cutibacterium acnes	0.86638	6542	19934	22690768
ERR6913216	Severe acute respiratory syndrome-related coronavirus	0.77822	7797	39552	17198782
ERR6913199	Severe acute respiratory syndrome-related coronavirus	0.75690	439	62396	20758064
ERR6913221	Severe acute respiratory syndrome-related coronavirus	0.73823	4360	23570	19171612
ERR6913314	Klebsiella pneumoniae	0.72546	756611	2148206	21206122
ERR6913173	Cutibacterium acnes	0.71600	3111	27156	21165410
ERR6913255	Cutibacterium acnes	0.65390	495	2708	21873400
ERR6913303	Staphylococcus aureus	0.62618	597928	2139748	20103510
ERR6913332	Staphylococcus aureus	0.61502	684696	2489352	24091268
ERR6913117	Cutibacterium acnes	0.61149	362	397186	24205196
ERR6913111	Cutibacterium acnes	0.61069	160	33240	27646936
ERR6913211	Cutibacterium acnes	0.59885	312	39562	17691576
ERR6913212	Cutibacterium acnes	0.57619	363	6948	20644176
ERR6913219	Corynebacterium propinquum	0.56391	153136	615136	18437710
ERR6913168	Haemophilus influenzae	0.53107	2743	142662	20396446
ERR6913261	Corynebacterium tuberculostearicum	0.51247	370	8410	24026306
ERR6913207	Cutibacterium acnes	0.50299	84	9240	25216066
ERR6913127	Dolosigranulum pigrum	0.48795	2652	30170	19048514
ERR6913181	Streptococcus salivarius	0.47683	461431	2252564	19977940
ERR6913104	Stenotrophomonas maltophilia	0.47353	79533	610606	22910206
ERR6913223	Dolosigranulum pigrum	0.46865	265649	1173894	21573718
ERR6913322	Klebsiella pneumoniae	0.45093	534153	2441696	11522192
ERR6913103	Cutibacterium acnes	0.44541	359	385740	21364260
ERR6913262	Pseudolabrys sp. FHR47	0.44188	5368	30798	20341522
ERR6913208	Moraxella nonliquefaciens	0.43645	19969	109226	17354398
⋮	⋮	⋮	⋮	⋮	⋮
ERR6913204	Moraxella osloensis	0.10701	1509	47600	27571556
ERR6913298	Neisseria mucosa	0.10699	4528	364136	19913788
ERR6913210	Cutibacterium acnes	0.10698	1590	107788	21965834
ERR6913271	Moraxella nonliquefaciens	0.10673	50585	1309086	23805264
ERR6913236	Prevotella veroralis	0.10667	152080	3303920	15718784
ERR6913196	Veillonella atypica	0.10632	85977	2236474	22682382
ERR6913278	Veillonella parvula	0.10595	134990	2714728	20047904
ERR6913291	Veillonella parvula	0.10593	127399	2739370	26470190
ERR6913343	Neisseria meningitidis	0.10547	180856	3478632	41696524
ERR6913103	Corynebacterium kefirresidentii	0.10546	85	385740	21364260
ERR6913265	Mycoplasmoides pneumoniae	0.10545	180	34894	15157352
ERR6913345	Streptococcus agalactiae	0.10536	116804	2750394	21714858
ERR6913342	Streptococcus salivarius	0.10533	193304	3754758	17613434
ERR6913271	Prevotella melaninogenica	0.10480	49670	1309086	23805264
ERR6913106	Lacticaseibacillus paracasei	0.10349	37796	1271618	23398900
ERR6913136	Prevotella veroralis	0.10343	89995	2239760	20026148
ERR6913312	Rothia mucilaginosa	0.10334	20096	1001132	18705528
ERR6913280	Veillonella parvula	0.10314	148136	3018286	17282568
ERR6913274	Babesia bigemina	0.10307	494	47250	16381626
ERR6913125	Shewanella algae	0.10297	142	151202	16206168
ERR6913260	Phaeodactylum tricornutum	0.10284	170	27568	20149704
ERR6913251	Burkholderia multivorans	0.10269	103	9458	25147866
ERR6913243	Streptococcus agalactiae	0.10265	130716	2851368	17773492
ERR6913114	Vibrio plantisponsor	0.10182	888	299664	17624856
ERR6913280	Leptotrichia wadei	0.10179	146196	3018286	17282568
ERR6913345	Veillonella parvula	0.10169	112729	2750394	21714858
ERR6913193	Rothia mucilaginosa	0.10168	34753	812494	21176470
ERR6913323	Streptococcus australis	0.10100	83717	3066570	19424544
ERR6913265	Homo sapiens	0.10076	172	34894	15157352
ERR6913266	Streptococcus sanguinis	0.10005	189	9030	22310726

abun_long %>%
 select(run_accession, taxon_name, fraction_total_reads, new_est_reads, read_count, total_reads) %>%
 filter(fraction_total_reads>0.1) %>%
 arrange(desc(fraction_total_reads)) %>% 
 slice_head(n=10)

A tibble: 10 × 6

run_accession	taxon_name	fraction_total_reads	new_est_reads	read_count	total_reads
<chr>	<chr>	<dbl>	<int>	<int>	<int>
ERR6913115	Cutibacterium acnes	1.00000	79	33254	18306476
ERR6913154	Haemophilus influenzae	0.98190	15187	39244	18749066
ERR6913269	Influenza A virus	0.97180	11614	25426	23544470
ERR6913264	Haemophilus influenzae	0.92120	4618	21382	18079420
ERR6913250	Haemophilus influenzae	0.88349	73565	169548	18898684
ERR6913252	Cutibacterium acnes	0.86638	6542	19934	22690768
ERR6913216	Severe acute respiratory syndrome-related coronavirus	0.77822	7797	39552	17198782
ERR6913199	Severe acute respiratory syndrome-related coronavirus	0.75690	439	62396	20758064
ERR6913221	Severe acute respiratory syndrome-related coronavirus	0.73823	4360	23570	19171612
ERR6913314	Klebsiella pneumoniae	0.72546	756611	2148206	21206122

abun_long <- abun_long %>% 
    mutate(fraction_nonhuman_reads=new_est_reads/read_count,
           fraction_human_nonhuman_reads=new_est_reads/total_reads)

abun_long %>% 
 slice_head(n=10)

A tibble: 10 × 20

run_accession	taxon_name	taxonomy_id	taxonomy_lvl	kraken_assigned_reads	added_reads	new_est_reads	fraction_total_reads	host_subject_id	patient_code	nuc	host_body_site	host_disease_status	miscellaneous_parameter	Ct	total_reads	read_count	base_count	fraction_nonhuman_reads	fraction_human_nonhuman_reads
<chr>	<chr>	<int>	<chr>	<int>	<int>	<int>	<dbl>	<chr>	<chr>	<chr>	<chr>	<chr>	<chr>	<dbl>	<int>	<int>	<int>	<dbl>	<dbl>
ERR6913112	Streptococcus oralis	1303	S	315	139	454	0.04101	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0071559170	1.777348e-05
ERR6913112	Streptococcus sp. LPB0220	2610896	S	64	14	78	0.00705	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0012294307	3.053593e-06
ERR6913112	Streptococcus sp. HSISM1	1316408	S	50	10	60	0.00542	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0009457159	2.348917e-06
ERR6913112	Streptococcus sp. oral taxon 064	712624	S	14	21	35	0.00316	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0005516676	1.370202e-06
ERR6913112	Streptococcus sp. oral taxon 061	712623	S	11	1	12	0.00108	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0001891432	4.697835e-07
ERR6913112	Streptococcus salivarius	1304	S	171	60	231	0.02087	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0036410062	9.043332e-06
ERR6913112	Streptococcus mitis	28037	S	135	24	159	0.01436	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0025061472	6.224631e-06
ERR6913112	Streptococcus intermedius	1338	S	106	32	138	0.01246	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0021751466	5.402510e-06
ERR6913112	Streptococcus vestibularis	1343	S	69	10	79	0.00714	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0012451926	3.092741e-06
ERR6913112	Streptococcus parasanguinis	1318	S	59	9	68	0.00614	P259_DNA_S4_L001	P259	DNA	Nasopharyngeal	SARS-CoV-2 positive	Symptomatic-DNA-sequenced	19.95	25543682	63444	8094624	0.0010718114	2.662106e-06

abun_long %>% select(run_accession,fraction_total_reads) %>% group_by(run_accession) %>% summarise(sum(fraction_total_reads))

A tibble: 198 × 2

run_accession	sum(fraction_total_reads)
<chr>	<dbl>
ERR6913101	0.99698
ERR6913102	0.99527
ERR6913103	0.99008
ERR6913104	0.99840
ERR6913106	0.99967
ERR6913107	0.99770
ERR6913108	0.99640
ERR6913109	0.99193
ERR6913111	0.98855
ERR6913112	0.99706
ERR6913113	0.99214
ERR6913114	0.99702
ERR6913115	1.00000
ERR6913116	0.99427
ERR6913117	0.99325
ERR6913118	0.99824
ERR6913120	0.99409
ERR6913121	0.99418
ERR6913122	0.99866
ERR6913123	0.99718
ERR6913124	0.99848
ERR6913125	0.99493
ERR6913126	0.99461
ERR6913127	0.99907
ERR6913128	0.99973
ERR6913129	1.00280
ERR6913130	0.99255
ERR6913131	1.00045
ERR6913132	0.99916
ERR6913133	0.99783
⋮	⋮
ERR6913307	0.99956
ERR6913308	0.99985
ERR6913312	0.99855
ERR6913313	0.99983
ERR6913314	0.99986
ERR6913315	0.99843
ERR6913316	0.99748
ERR6913320	0.99839
ERR6913322	0.99989
ERR6913323	0.99959
ERR6913324	0.99565
ERR6913325	0.99925
ERR6913326	0.99967
ERR6913327	0.99944
ERR6913328	0.99818
ERR6913329	0.99841
ERR6913330	0.99901
ERR6913331	0.99833
ERR6913332	0.99981
ERR6913333	0.99990
ERR6913334	0.99972
ERR6913335	0.99959
ERR6913336	0.99965
ERR6913337	0.99989
ERR6913341	1.00040
ERR6913342	1.00012
ERR6913343	0.99989
ERR6913344	0.99969
ERR6913345	0.99962
ERR6913349	0.99994

SARS_CoV-2
taxon_name = Severe acute respiratory syndrome-related coronavirus
taxonomy_id = 694009

sars_abun <- abun_long %>% select(run_accession, taxon_name, taxonomy_id,fraction_total_reads,Ct,fraction_nonhuman_reads,host_disease_status) %>% 
  filter(taxonomy_id==694009) %>% 
  arrange(desc(fraction_nonhuman_reads))

slice_head(sars_abun,n=20)

A tibble: 20 × 7

run_accession	taxon_name	taxonomy_id	fraction_total_reads	Ct	fraction_nonhuman_reads	host_disease_status
<chr>	<chr>	<int>	<dbl>	<dbl>	<dbl>	<chr>
ERR6913216	Severe acute respiratory syndrome-related coronavirus	694009	0.77822	17.99	0.1971328883	SARS-CoV-2 positive
ERR6913221	Severe acute respiratory syndrome-related coronavirus	694009	0.73823	17.88	0.1849809079	SARS-CoV-2 positive
ERR6913214	Severe acute respiratory syndrome-related coronavirus	694009	0.38784	17.81	0.0576540004	SARS-CoV-2 positive
ERR6913210	Severe acute respiratory syndrome-related coronavirus	694009	0.41324	19.52	0.0569822244	SARS-CoV-2 positive
ERR6913204	Severe acute respiratory syndrome-related coronavirus	694009	0.17501	18.42	0.0518487395	SARS-CoV-2 positive
ERR6913203	Severe acute respiratory syndrome-related coronavirus	694009	0.21930	19.38	0.0412597045	SARS-CoV-2 positive
ERR6913217	Severe acute respiratory syndrome-related coronavirus	694009	0.19576	17.56	0.0292371171	SARS-CoV-2 positive
ERR6913215	Severe acute respiratory syndrome-related coronavirus	694009	0.22142	18.89	0.0278418723	SARS-CoV-2 positive
ERR6913219	Severe acute respiratory syndrome-related coronavirus	694009	0.04292	17.93	0.0189486553	SARS-CoV-2 positive
ERR6913197	Severe acute respiratory syndrome-related coronavirus	694009	0.04034	18.00	0.0118457155	SARS-CoV-2 positive
ERR6913208	Severe acute respiratory syndrome-related coronavirus	694009	0.02116	19.95	0.0088623588	SARS-CoV-2 positive
ERR6913220	Severe acute respiratory syndrome-related coronavirus	694009	0.01979	19.64	0.0085605285	SARS-CoV-2 positive
ERR6913199	Severe acute respiratory syndrome-related coronavirus	694009	0.75690	18.81	0.0070357074	SARS-CoV-2 positive
ERR6913218	Severe acute respiratory syndrome-related coronavirus	694009	0.01710	17.55	0.0053494982	SARS-CoV-2 positive
ERR6913211	Severe acute respiratory syndrome-related coronavirus	694009	0.28791	19.63	0.0037915171	SARS-CoV-2 positive
ERR6913200	Severe acute respiratory syndrome-related coronavirus	694009	0.00751	18.02	0.0034187199	SARS-CoV-2 positive
ERR6913212	Severe acute respiratory syndrome-related coronavirus	694009	0.03651	23.43	0.0033103051	SARS-CoV-2 positive
ERR6913327	Severe acute respiratory syndrome-related coronavirus	694009	0.00320	23.37	0.0013253006	SARS-CoV-2 positive
ERR6913209	Severe acute respiratory syndrome-related coronavirus	694009	0.00753	23.92	0.0008567145	SARS-CoV-2 positive
ERR6913121	Severe acute respiratory syndrome-related coronavirus	694009	0.00777	17.56	0.0006381674	SARS-CoV-2 positive

abun_long %>% select(run_accession, taxon_name, taxonomy_id,fraction_total_reads,Ct,fraction_nonhuman_reads,host_disease_status) %>% 
  filter(grepl("corona",taxon_name,fixed = TRUE)) %>% 
  arrange(desc(fraction_nonhuman_reads))

A tibble: 72 × 7

run_accession	taxon_name	taxonomy_id	fraction_total_reads	Ct	fraction_nonhuman_reads	host_disease_status
<chr>	<chr>	<int>	<dbl>	<dbl>	<dbl>	<chr>
ERR6913216	Severe acute respiratory syndrome-related coronavirus	694009	0.77822	17.99	0.1971328883	SARS-CoV-2 positive
ERR6913221	Severe acute respiratory syndrome-related coronavirus	694009	0.73823	17.88	0.1849809079	SARS-CoV-2 positive
ERR6913214	Severe acute respiratory syndrome-related coronavirus	694009	0.38784	17.81	0.0576540004	SARS-CoV-2 positive
ERR6913210	Severe acute respiratory syndrome-related coronavirus	694009	0.41324	19.52	0.0569822244	SARS-CoV-2 positive
ERR6913204	Severe acute respiratory syndrome-related coronavirus	694009	0.17501	18.42	0.0518487395	SARS-CoV-2 positive
ERR6913203	Severe acute respiratory syndrome-related coronavirus	694009	0.21930	19.38	0.0412597045	SARS-CoV-2 positive
ERR6913217	Severe acute respiratory syndrome-related coronavirus	694009	0.19576	17.56	0.0292371171	SARS-CoV-2 positive
ERR6913215	Severe acute respiratory syndrome-related coronavirus	694009	0.22142	18.89	0.0278418723	SARS-CoV-2 positive
ERR6913219	Severe acute respiratory syndrome-related coronavirus	694009	0.04292	17.93	0.0189486553	SARS-CoV-2 positive
ERR6913197	Severe acute respiratory syndrome-related coronavirus	694009	0.04034	18.00	0.0118457155	SARS-CoV-2 positive
ERR6913208	Severe acute respiratory syndrome-related coronavirus	694009	0.02116	19.95	0.0088623588	SARS-CoV-2 positive
ERR6913220	Severe acute respiratory syndrome-related coronavirus	694009	0.01979	19.64	0.0085605285	SARS-CoV-2 positive
ERR6913199	Severe acute respiratory syndrome-related coronavirus	694009	0.75690	18.81	0.0070357074	SARS-CoV-2 positive
ERR6913218	Severe acute respiratory syndrome-related coronavirus	694009	0.01710	17.55	0.0053494982	SARS-CoV-2 positive
ERR6913252	Human coronavirus HKU1	290028	0.01059	0.00	0.0040132437	SARS-CoV-2 negative
ERR6913211	Severe acute respiratory syndrome-related coronavirus	694009	0.28791	19.63	0.0037915171	SARS-CoV-2 positive
ERR6913200	Severe acute respiratory syndrome-related coronavirus	694009	0.00751	18.02	0.0034187199	SARS-CoV-2 positive
ERR6913212	Severe acute respiratory syndrome-related coronavirus	694009	0.03651	23.43	0.0033103051	SARS-CoV-2 positive
ERR6913261	Human coronavirus NL63	277944	0.02909	0.00	0.0024970273	SARS-CoV-2 negative
ERR6913327	Severe acute respiratory syndrome-related coronavirus	694009	0.00320	23.37	0.0013253006	SARS-CoV-2 positive
ERR6913209	Severe acute respiratory syndrome-related coronavirus	694009	0.00753	23.92	0.0008567145	SARS-CoV-2 positive
ERR6913121	Severe acute respiratory syndrome-related coronavirus	694009	0.00777	17.56	0.0006381674	SARS-CoV-2 positive
ERR6913330	Severe acute respiratory syndrome-related coronavirus	694009	0.00159	19.55	0.0005329715	SARS-CoV-2 positive
ERR6913326	Severe acute respiratory syndrome-related coronavirus	694009	0.00092	20.29	0.0003524103	SARS-CoV-2 positive
ERR6913213	Severe acute respiratory syndrome-related coronavirus	694009	0.04115	21.34	0.0003137944	SARS-CoV-2 positive
ERR6913275	Severe acute respiratory syndrome-related coronavirus	694009	0.00063	27.65	0.0002771536	SARS-CoV-2 negative
ERR6913329	Severe acute respiratory syndrome-related coronavirus	694009	0.00102	24.73	0.0002373196	SARS-CoV-2 positive
ERR6913322	Severe acute respiratory syndrome-related coronavirus	694009	0.00044	17.53	0.0002117381	SARS-CoV-2 positive
ERR6913101	Severe acute respiratory syndrome-related coronavirus	694009	0.00106	18.00	0.0001944497	SARS-CoV-2 positive
ERR6913268	Severe acute respiratory syndrome-related coronavirus	694009	0.00140	0.00	0.0001807624	SARS-CoV-2 negative
⋮	⋮	⋮	⋮	⋮	⋮	⋮
ERR6913328	Severe acute respiratory syndrome-related coronavirus	694009	0.00069	25.72	9.325615e-05	SARS-CoV-2 positive
ERR6913223	Severe acute respiratory syndrome-related coronavirus	694009	0.00019	22.18	8.944590e-05	SARS-CoV-2 positive
ERR6913334	Severe acute respiratory syndrome-related coronavirus	694009	0.00013	0.00	5.814844e-05	SARS-CoV-2 negative
ERR6913104	Severe acute respiratory syndrome-related coronavirus	694009	0.00017	18.02	4.749380e-05	SARS-CoV-2 positive
ERR6913312	Severe acute respiratory syndrome-related coronavirus	694009	0.00020	0.00	3.895590e-05	SARS-CoV-2 negative
ERR6913202	Severe acute respiratory syndrome-related coronavirus	694009	0.00009	19.59	3.882656e-05	SARS-CoV-2 positive
ERR6913332	Severe acute respiratory syndrome-related coronavirus	694009	0.00008	19.51	3.615399e-05	SARS-CoV-2 positive
ERR6913295	Severe acute respiratory syndrome-related coronavirus	694009	0.00019	25.64	2.455337e-05	SARS-CoV-2 positive
ERR6913324	Severe acute respiratory syndrome-related coronavirus	694009	0.00019	25.64	2.455337e-05	SARS-CoV-2 positive
ERR6913333	Severe acute respiratory syndrome-related coronavirus	694009	0.00005	23.52	2.190989e-05	SARS-CoV-2 positive
ERR6913242	Severe acute respiratory syndrome-related coronavirus	694009	0.00007	NA	1.935648e-05	SARS-CoV-2 positive
ERR6913345	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.453191e-06	SARS-CoV-2 negative
ERR6913342	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.055177e-06	SARS-CoV-2 negative
ERR6913276	Severe acute respiratory syndrome-related coronavirus	694009	0.00003	21.94	8.181380e-06	SARS-CoV-2 negative
ERR6913306	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	8.055400e-06	SARS-CoV-2 negative
ERR6913222	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	17.28	7.086245e-06	SARS-CoV-2 positive
ERR6913276	Pseudomonas coronafaciens	53409	0.00002	21.94	6.608038e-06	SARS-CoV-2 negative
ERR6913323	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	22.39	6.521945e-06	SARS-CoV-2 positive
ERR6913313	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	6.085766e-06	SARS-CoV-2 negative
ERR6913325	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	24.14	5.481789e-06	SARS-CoV-2 positive
ERR6913271	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	NA	4.583351e-06	SARS-CoV-2 negative
ERR6913307	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	0.00	3.998637e-06	SARS-CoV-2 negative
ERR6913343	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	0.00	3.162163e-06	SARS-CoV-2 negative
ERR6913196	Pseudomonas coronafaciens	53409	0.00001	18.29	3.129927e-06	SARS-CoV-2 negative
ERR6913228	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	25.21	2.175078e-06	SARS-CoV-2 positive
ERR6913344	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	0.00	2.100279e-06	SARS-CoV-2 negative
ERR6913194	Pseudomonas coronafaciens	53409	0.00000	27.00	1.442673e-06	SARS-CoV-2 negative
ERR6913290	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	27.00	7.818156e-07	SARS-CoV-2 negative
ERR6913292	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	18.29	7.401070e-07	SARS-CoV-2 negative
ERR6913225	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	22.55	3.665864e-07	SARS-CoV-2 positive

library("ggplot2")
library("ggpubr")

ggscatter(sars_abun, x = "fraction_nonhuman_reads", y = "Ct",
           add="reg.line", add.params = list(color = "#00bfc4"),
           conf.int = FALSE,
           cor.coef = TRUE,
           cor.coeff.args = list(method = "spearman"),
           #cor.method = "spearman",
           ggtheme = theme_classic(),
           #add = "reg.line", add.params = c(color = '#00bfc4'),
           title = "Ct - fraction_nonhuman_reads", xlab = "fraction_nonhuman_reads", ylab = "Ct",
           font.tickslab = c(size=15, color = "black"), font.main = 20,font.y = 15, font.x = 15)

`geom_smooth()` using formula 'y ~ x'

Warning message:
“Removed 3 rows containing non-finite values (stat_smooth).”
Warning message:
“Removed 3 rows containing non-finite values (stat_cor).”
Warning message:
“Removed 3 rows containing missing values (geom_point).”

colnames(abun_long)

1. 'run_accession'
2. 'taxon_name'
3. 'taxonomy_id'
4. 'taxonomy_lvl'
5. 'kraken_assigned_reads'
6. 'added_reads'
7. 'new_est_reads'
8. 'fraction_total_reads'
9. 'host_subject_id'
10. 'patient_code'
11. 'nuc'
12. 'host_body_site'
13. 'host_disease_status'
14. 'miscellaneous_parameter'
15. 'Ct'
16. 'total_reads'
17. 'read_count'
18. 'base_count'
19. 'fraction_nonhuman_reads'
20. 'fraction_human_nonhuman_reads'

Check if there are any SARS-CoV-2 negative patient express SARS-CoV-2

abun_long %>% select(run_accession, taxon_name, taxonomy_id,fraction_total_reads,Ct,fraction_nonhuman_reads,host_disease_status) %>% 
  filter(taxonomy_id==694009 & host_disease_status =="SARS-CoV-2 negative")
  #arrange(desc(fraction_nonhuman_reads))

A tibble: 19 × 7

run_accession	taxon_name	taxonomy_id	fraction_total_reads	Ct	fraction_nonhuman_reads	host_disease_status
<chr>	<chr>	<int>	<dbl>	<dbl>	<dbl>	<chr>
ERR6913276	Severe acute respiratory syndrome-related coronavirus	694009	0.00003	21.94	8.181380e-06	SARS-CoV-2 negative
ERR6913275	Severe acute respiratory syndrome-related coronavirus	694009	0.00063	27.65	2.771536e-04	SARS-CoV-2 negative
ERR6913271	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	NA	4.583351e-06	SARS-CoV-2 negative
ERR6913305	Severe acute respiratory syndrome-related coronavirus	694009	0.00046	0.00	1.590100e-04	SARS-CoV-2 negative
ERR6913334	Severe acute respiratory syndrome-related coronavirus	694009	0.00013	0.00	5.814844e-05	SARS-CoV-2 negative
ERR6913306	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	8.055400e-06	SARS-CoV-2 negative
ERR6913307	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	0.00	3.998637e-06	SARS-CoV-2 negative
ERR6913345	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.453191e-06	SARS-CoV-2 negative
ERR6913312	Severe acute respiratory syndrome-related coronavirus	694009	0.00020	0.00	3.895590e-05	SARS-CoV-2 negative
ERR6913315	Severe acute respiratory syndrome-related coronavirus	694009	0.00053	0.00	1.124646e-04	SARS-CoV-2 negative
ERR6913343	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	0.00	3.162163e-06	SARS-CoV-2 negative
ERR6913344	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	0.00	2.100279e-06	SARS-CoV-2 negative
ERR6913254	Severe acute respiratory syndrome-related coronavirus	694009	0.00226	0.00	1.701702e-04	SARS-CoV-2 negative
ERR6913313	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	6.085766e-06	SARS-CoV-2 negative
ERR6913342	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.055177e-06	SARS-CoV-2 negative
ERR6913267	Severe acute respiratory syndrome-related coronavirus	694009	0.00242	0.00	1.415194e-04	SARS-CoV-2 negative
ERR6913268	Severe acute respiratory syndrome-related coronavirus	694009	0.00140	0.00	1.807624e-04	SARS-CoV-2 negative
ERR6913290	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	27.00	7.818156e-07	SARS-CoV-2 negative
ERR6913292	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	18.29	7.401070e-07	SARS-CoV-2 negative

Check is SARS-CoV-2 only ever seen in RNA samples (ie not in DNA samples)?

abun_long %>% select(run_accession, taxon_name, taxonomy_id,fraction_total_reads,Ct,fraction_nonhuman_reads,host_disease_status,nuc) %>% 
  filter(taxonomy_id==694009 & nuc=="RNA")

A tibble: 54 × 8

run_accession	taxon_name	taxonomy_id	fraction_total_reads	Ct	fraction_nonhuman_reads	host_disease_status	nuc
<chr>	<chr>	<int>	<dbl>	<dbl>	<dbl>	<chr>	<chr>
ERR6913209	Severe acute respiratory syndrome-related coronavirus	694009	0.00753	23.92	8.567145e-04	SARS-CoV-2 positive	RNA
ERR6913208	Severe acute respiratory syndrome-related coronavirus	694009	0.02116	19.95	8.862359e-03	SARS-CoV-2 positive	RNA
ERR6913218	Severe acute respiratory syndrome-related coronavirus	694009	0.01710	17.55	5.349498e-03	SARS-CoV-2 positive	RNA
ERR6913276	Severe acute respiratory syndrome-related coronavirus	694009	0.00003	21.94	8.181380e-06	SARS-CoV-2 negative	RNA
ERR6913197	Severe acute respiratory syndrome-related coronavirus	694009	0.04034	18.00	1.184572e-02	SARS-CoV-2 positive	RNA
ERR6913275	Severe acute respiratory syndrome-related coronavirus	694009	0.00063	27.65	2.771536e-04	SARS-CoV-2 negative	RNA
ERR6913222	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	17.28	7.086245e-06	SARS-CoV-2 positive	RNA
ERR6913324	Severe acute respiratory syndrome-related coronavirus	694009	0.00019	25.64	2.455337e-05	SARS-CoV-2 positive	RNA
ERR6913327	Severe acute respiratory syndrome-related coronavirus	694009	0.00320	23.37	1.325301e-03	SARS-CoV-2 positive	RNA
ERR6913328	Severe acute respiratory syndrome-related coronavirus	694009	0.00069	25.72	9.325615e-05	SARS-CoV-2 positive	RNA
ERR6913271	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	NA	4.583351e-06	SARS-CoV-2 negative	RNA
ERR6913326	Severe acute respiratory syndrome-related coronavirus	694009	0.00092	20.29	3.524103e-04	SARS-CoV-2 positive	RNA
ERR6913202	Severe acute respiratory syndrome-related coronavirus	694009	0.00009	19.59	3.882656e-05	SARS-CoV-2 positive	RNA
ERR6913199	Severe acute respiratory syndrome-related coronavirus	694009	0.75690	18.81	7.035707e-03	SARS-CoV-2 positive	RNA
ERR6913211	Severe acute respiratory syndrome-related coronavirus	694009	0.28791	19.63	3.791517e-03	SARS-CoV-2 positive	RNA
ERR6913213	Severe acute respiratory syndrome-related coronavirus	694009	0.04115	21.34	3.137944e-04	SARS-CoV-2 positive	RNA
ERR6913204	Severe acute respiratory syndrome-related coronavirus	694009	0.17501	18.42	5.184874e-02	SARS-CoV-2 positive	RNA
ERR6913212	Severe acute respiratory syndrome-related coronavirus	694009	0.03651	23.43	3.310305e-03	SARS-CoV-2 positive	RNA
ERR6913214	Severe acute respiratory syndrome-related coronavirus	694009	0.38784	17.81	5.765400e-02	SARS-CoV-2 positive	RNA
ERR6913334	Severe acute respiratory syndrome-related coronavirus	694009	0.00013	0.00	5.814844e-05	SARS-CoV-2 negative	RNA
ERR6913345	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.453191e-06	SARS-CoV-2 negative	RNA
ERR6913343	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	0.00	3.162163e-06	SARS-CoV-2 negative	RNA
ERR6913344	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	0.00	2.100279e-06	SARS-CoV-2 negative	RNA
ERR6913254	Severe acute respiratory syndrome-related coronavirus	694009	0.00226	0.00	1.701702e-04	SARS-CoV-2 negative	RNA
ERR6913200	Severe acute respiratory syndrome-related coronavirus	694009	0.00751	18.02	3.418720e-03	SARS-CoV-2 positive	RNA
ERR6913230	Severe acute respiratory syndrome-related coronavirus	694009	0.00032	23.01	1.213615e-04	SARS-CoV-2 positive	RNA
ERR6913228	Severe acute respiratory syndrome-related coronavirus	694009	0.00001	25.21	2.175078e-06	SARS-CoV-2 positive	RNA
ERR6913219	Severe acute respiratory syndrome-related coronavirus	694009	0.04292	17.93	1.894866e-02	SARS-CoV-2 positive	RNA
ERR6913210	Severe acute respiratory syndrome-related coronavirus	694009	0.41324	19.52	5.698222e-02	SARS-CoV-2 positive	RNA
ERR6913220	Severe acute respiratory syndrome-related coronavirus	694009	0.01979	19.64	8.560529e-03	SARS-CoV-2 positive	RNA
ERR6913217	Severe acute respiratory syndrome-related coronavirus	694009	0.19576	17.56	2.923712e-02	SARS-CoV-2 positive	RNA
ERR6913325	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	24.14	5.481789e-06	SARS-CoV-2 positive	RNA
ERR6913331	Severe acute respiratory syndrome-related coronavirus	694009	0.00047	25.49	1.182014e-04	SARS-CoV-2 positive	RNA
ERR6913333	Severe acute respiratory syndrome-related coronavirus	694009	0.00005	23.52	2.190989e-05	SARS-CoV-2 positive	RNA
ERR6913216	Severe acute respiratory syndrome-related coronavirus	694009	0.77822	17.99	1.971329e-01	SARS-CoV-2 positive	RNA
ERR6913221	Severe acute respiratory syndrome-related coronavirus	694009	0.73823	17.88	1.849809e-01	SARS-CoV-2 positive	RNA
ERR6913215	Severe acute respiratory syndrome-related coronavirus	694009	0.22142	18.89	2.784187e-02	SARS-CoV-2 positive	RNA
ERR6913322	Severe acute respiratory syndrome-related coronavirus	694009	0.00044	17.53	2.117381e-04	SARS-CoV-2 positive	RNA
ERR6913342	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	0.00	9.055177e-06	SARS-CoV-2 negative	RNA
ERR6913323	Severe acute respiratory syndrome-related coronavirus	694009	0.00002	22.39	6.521945e-06	SARS-CoV-2 positive	RNA
ERR6913267	Severe acute respiratory syndrome-related coronavirus	694009	0.00242	0.00	1.415194e-04	SARS-CoV-2 negative	RNA
ERR6913242	Severe acute respiratory syndrome-related coronavirus	694009	0.00007	NA	1.935648e-05	SARS-CoV-2 positive	RNA
ERR6913203	Severe acute respiratory syndrome-related coronavirus	694009	0.21930	19.38	4.125970e-02	SARS-CoV-2 positive	RNA
ERR6913233	Severe acute respiratory syndrome-related coronavirus	694009	0.00030	26.37	1.279669e-04	SARS-CoV-2 positive	RNA
ERR6913268	Severe acute respiratory syndrome-related coronavirus	694009	0.00140	0.00	1.807624e-04	SARS-CoV-2 negative	RNA
ERR6913205	Severe acute respiratory syndrome-related coronavirus	694009	0.00023	23.66	1.080517e-04	SARS-CoV-2 positive	RNA
ERR6913225	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	22.55	3.665864e-07	SARS-CoV-2 positive	RNA
ERR6913226	Severe acute respiratory syndrome-related coronavirus	694009	0.00035	NA	1.566321e-04	SARS-CoV-2 positive	RNA
ERR6913290	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	27.00	7.818156e-07	SARS-CoV-2 negative	RNA
ERR6913292	Severe acute respiratory syndrome-related coronavirus	694009	0.00000	18.29	7.401070e-07	SARS-CoV-2 negative	RNA
ERR6913329	Severe acute respiratory syndrome-related coronavirus	694009	0.00102	24.73	2.373196e-04	SARS-CoV-2 positive	RNA
ERR6913330	Severe acute respiratory syndrome-related coronavirus	694009	0.00159	19.55	5.329715e-04	SARS-CoV-2 positive	RNA
ERR6913332	Severe acute respiratory syndrome-related coronavirus	694009	0.00008	19.51	3.615399e-05	SARS-CoV-2 positive	RNA
ERR6913223	Severe acute respiratory syndrome-related coronavirus	694009	0.00019	22.18	8.944590e-05	SARS-CoV-2 positive	RNA

10 most ubiquitous human pathogens found in the 125 patients

abun_long %>% select(run_accession, taxon_name, taxonomy_id,fraction_nonhuman_reads) %>%
  group_by(taxon_name) %>%
  summarise(MAX = max(fraction_nonhuman_reads)) %>%
  arrange(desc(MAX)) %>% slice_head(n=10)

A tibble: 10 × 2

taxon_name	MAX
<chr>	<dbl>
Influenza A virus	0.4567765
Haemophilus influenzae	0.4338889
Klebsiella pneumoniae	0.3522060
Cutibacterium acnes	0.3281830
Staphylococcus aureus	0.2794385
Corynebacterium propinquum	0.2489466
Dolosigranulum pigrum	0.2262973
Streptococcus salivarius	0.2048470
Severe acute respiratory syndrome-related coronavirus	0.1971329
Moraxella nonliquefaciens	0.1828228

"wild" version

abun_wild <-
   abun_long %>% select(run_accession, taxon_name, fraction_nonhuman_reads) %>%
   pivot_wider(names_from = taxon_name, values_from = fraction_nonhuman_reads, values_fill = 0)

slice_head(abun_wild, n=5)

A tibble: 5 × 8601

run_accession	Streptococcus oralis	Streptococcus sp. LPB0220	Streptococcus sp. HSISM1	Streptococcus sp. oral taxon 064	Streptococcus sp. oral taxon 061	Streptococcus salivarius	Streptococcus mitis	Streptococcus intermedius	Streptococcus vestibularis	⋯	Staphylococcus sp. MZ9	Staphylococcus sp. MZ8	Chryseobacterium nepalense	Peeveelvirus CN125	Biseptimavirus bv23MRA	Biseptimavirus IME136101	Phietavirus pv3MRA	Staphylococcus sp. IVB6240	Sutcliffiella cohnii	Aeromonas sp. Ne-1
<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
ERR6913112	0.007155917	0.001229431	0.0009457159	5.516676e-04	0.0001891432	0.003641006	0.002506147	2.175147e-03	0.0012451926	⋯	0	0	0	0	0	0	0	0	0	0
ERR6913113	0.000000000	0.000000000	0.0000000000	0.000000e+00	0.0000000000	0.000000000	0.000000000	0.000000e+00	0.0000000000	⋯	0	0	0	0	0	0	0	0	0	0
ERR6913320	0.003536297	0.007010695	0.0067006618	9.391706e-05	0.0019599849	0.003821250	0.007972277	1.787626e-04	0.0002022418	⋯	0	0	0	0	0	0	0	0	0	0
ERR6913209	0.000000000	0.000000000	0.0000000000	0.000000e+00	0.0000000000	0.000000000	0.000000000	0.000000e+00	0.0000000000	⋯	0	0	0	0	0	0	0	0	0	0
ERR6913122	0.001556366	0.002671314	0.0027679163	5.232610e-05	0.0015080649	0.015328863	0.002059501	7.513491e-05	0.0001194108	⋯	0	0	0	0	0	0	0	0	0	0

abun_wild_taxon <-
   abun_long %>% select(run_accession, taxon_name, fraction_nonhuman_reads) %>%
   pivot_wider(names_from = run_accession, values_from = fraction_nonhuman_reads, values_fill = 0)

slice_head(abun_wild_taxon, n=5)

A tibble: 5 × 199

taxon_name	ERR6913112	ERR6913113	ERR6913320	ERR6913209	ERR6913122	ERR6913208	ERR6913218	ERR6913349	ERR6913179	⋯	ERR6913290	ERR6913292	ERR6913300	ERR6913329	ERR6913301	ERR6913330	ERR6913303	ERR6913332	ERR6913127	ERR6913223
<chr>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
Streptococcus oralis	0.0071559170	0	3.536297e-03	0	0.0015563659	0	0.002035742	4.490799e-04	2.545224e-03	⋯	0.0019736935	0.0013114696	3.211530e-03	0.0006910871	2.970500e-03	1.011372e-03	3.771005e-03	0.0033699533	0	0.0001158537
Streptococcus sp. LPB0220	0.0012294307	0	7.010695e-03	0	0.0026713143	0	0.004570818	6.347872e-04	3.729943e-03	⋯	0.0009987694	0.0017903188	6.110143e-03	0.0033781329	7.908116e-04	5.050799e-04	5.432415e-03	0.0045345134	0	0.0000000000
Streptococcus sp. HSISM1	0.0009457159	0	6.700662e-03	0	0.0027679163	0	0.004249569	3.579486e-04	3.554157e-03	⋯	0.0008807153	0.0013018482	5.755463e-03	0.0026507134	7.324369e-04	3.553143e-04	4.838888e-03	0.0033096967	0	0.0000000000
Streptococcus sp. oral taxon 064	0.0005516676	0	9.391706e-05	0	0.0000523261	0	0.000000000	1.785045e-05	5.200102e-05	⋯	0.0001203996	0.0001572727	8.293513e-05	0.0000000000	8.150426e-05	6.972892e-05	6.776499e-05	0.0001084620	0	0.0000000000
Streptococcus sp. oral taxon 061	0.0001891432	0	1.959985e-03	0	0.0015080649	0	0.002084628	1.525118e-04	3.541722e-03	⋯	0.0010972782	0.0003500706	4.134993e-04	0.0001468753	7.390454e-04	2.067614e-04	1.416989e-03	0.0005925237	0	0.0000000000

Heatmap visualisation of the abundance matrix

options(repr.plot.width=20, repr.plot.height=15)
abun_long %>%
 filter(str_detect(taxon_name,"corona")) %>%
 arrange(nuc, fraction_total_reads)  %>%
 select(run_accession, taxon_name, new_est_reads,fraction_total_reads,Ct,fraction_nonhuman_reads,host_disease_status,miscellaneous_parameter,nuc,host_subject_id) %>%
ggplot(aes(host_subject_id, taxon_name, fill=log2(fraction_total_reads))) +
 geom_raster(hjust = 0, vjust = 0)

library("heatmaply")
library(RColorBrewer)

Loading required package: plotly


Attaching package: ‘plotly’


The following object is masked from ‘package:ggplot2’:

    last_plot


The following object is masked from ‘package:stats’:

    filter


The following object is masked from ‘package:graphics’:

    layout


Loading required package: viridis

Loading required package: viridisLite


======================
Welcome to heatmaply version 1.3.0

Type citation('heatmaply') for how to cite the package.
Type ?heatmaply for the main documentation.

The github page is: https://github.com/talgalili/heatmaply/
Please submit your suggestions and bug-reports at: https://github.com/talgalili/heatmaply/issues
You may ask questions at stackoverflow, use the r and heatmaply tags: 
	 https://stackoverflow.com/questions/tagged/heatmaply
======================

abun_wild_taxon %>%
 column_to_rownames(var="taxon_name") %>%
 head(100) %>% mutate_if(is.numeric, ~ifelse(abs(.) == 0,0.0001,.)) %>% 
 mutate_if(is_double,log2)

A data.frame: 100 × 198

	ERR6913112	ERR6913113	ERR6913320	ERR6913209	ERR6913122	ERR6913208	ERR6913218	ERR6913349	ERR6913179	ERR6913180	⋯	ERR6913290	ERR6913292	ERR6913300	ERR6913329	ERR6913301	ERR6913330	ERR6913303	ERR6913332	ERR6913127	ERR6913223
	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	⋯	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
Streptococcus oralis	-7.126648	-13.28771	-8.143545	-13.28771	-9.327603	-13.287712	-8.940229	-11.120740	-8.617992	-7.488157	⋯	-8.984886	-9.574600	-8.282523	-10.498845	-8.395079	-9.949470	-8.050835	-8.213056	-13.287712	-13.075408
Streptococcus sp. LPB0220	-9.667794	-13.28771	-7.156227	-13.28771	-8.548235	-13.287712	-7.773332	-10.621439	-8.066631	-11.495246	⋯	-9.967561	-9.125568	-7.354578	-8.209558	-10.304378	-10.951201	-7.524190	-7.784837	-13.287712	-13.287712
Streptococcus sp. HSISM1	-10.046306	-13.28771	-7.221481	-13.28771	-8.496984	-13.287712	-7.878468	-11.447960	-8.136277	-11.361815	⋯	-10.149037	-9.585223	-7.440852	-8.559404	-10.415008	-11.458617	-7.691109	-8.239085	-13.287712	-13.287712
Streptococcus sp. oral taxon 064	-10.823913	-13.28771	-13.378253	-13.28771	-14.222110	-13.287712	-13.287712	-15.773680	-14.231100	-13.264887	⋯	-13.019882	-12.634444	-13.557657	-13.287712	-13.582765	-13.807883	-13.849100	-13.170523	-13.287712	-13.287712
Streptococcus sp. oral taxon 061	-12.368234	-13.28771	-8.994942	-13.28771	-9.373086	-13.287712	-8.905994	-12.678792	-8.141333	-7.095315	⋯	-9.831855	-11.480066	-11.239828	-12.733120	-10.402049	-12.239745	-9.462955	-10.720840	-13.287712	-13.287712
Streptococcus salivarius	-8.101447	-13.28771	-8.031740	-13.28771	-6.027606	-13.287712	-5.216751	-9.990480	-4.794457	-6.271805	⋯	-5.765467	-8.787154	-6.677531	-9.332870	-6.390139	-5.956515	-6.171271	-7.843794	-13.287712	-13.107588
Streptococcus mitis	-8.640313	-13.28771	-6.970792	-13.28771	-8.923489	-13.287712	-8.574912	-11.011312	-7.707027	-6.030782	⋯	-7.413416	-7.888510	-8.354856	-10.623496	-5.996077	-8.058582	-9.147896	-10.003570	-9.926631	-14.462431
Streptococcus intermedius	-8.844672	-13.28771	-12.449668	-13.28771	-13.700157	-13.287712	-13.604019	-15.416745	-11.760309	-13.108442	⋯	-14.116743	-9.965951	-14.010708	-15.495621	-12.057509	-13.833194	-13.910068	-14.465979	-13.287712	-13.287712
Streptococcus vestibularis	-9.649415	-13.28771	-12.271631	-13.28771	-13.031779	-13.287712	-11.718190	-16.321167	-12.223281	-11.758280	⋯	-13.642812	-15.257238	-12.883427	-15.444995	-14.237630	-15.038664	-13.122119	-14.708180	-13.287712	-13.287712
Streptococcus parasanguinis	-9.865733	-13.28771	-6.499993	-13.28771	-6.610045	-13.287712	-5.935288	-10.732357	-6.192241	-10.485956	⋯	-8.057249	-8.967286	-6.446170	-7.406076	-9.405278	-9.918664	-7.444047	-7.662494	-13.287712	-13.287712
Streptococcus gordonii	-10.070553	-13.28771	-11.009548	-13.28771	-12.298059	-13.287712	-11.455156	-15.197179	-11.820972	-10.177798	⋯	-11.187320	-13.446900	-11.514814	-13.055048	-12.044026	-13.576558	-11.089430	-11.529662	-13.287712	-13.287712
Streptococcus pneumoniae	-10.560879	-13.28771	-7.645700	-13.28771	-8.936708	-13.287712	-7.707621	-9.596042	-8.889316	-6.747209	⋯	-6.460120	-7.302705	-9.342959	-8.631435	-6.953211	-6.634478	-9.273287	-9.547333	-13.287712	-14.407983
Streptococcus mutans	-11.309340	-13.28771	-13.462645	-13.28771	-15.807072	-13.287712	-13.287712	-13.287712	-15.667200	-14.632004	⋯	-16.038741	-16.278300	-14.112246	-15.910658	-13.909575	-14.898486	-11.264138	-13.165190	-13.287712	-13.287712
Streptococcus infantis	-11.429634	-13.28771	-8.184840	-13.28771	-8.534532	-13.287712	-8.080457	-11.823571	-9.516258	-9.646938	⋯	-10.752365	-11.775176	-10.459999	-11.612978	-9.133114	-11.074057	-10.332911	-11.086207	-13.287712	-13.287712
Streptococcus gwangjuense	-11.493764	-13.28771	-10.670267	-13.28771	-12.588649	-13.287712	-12.320226	-14.825210	-11.471574	-10.013952	⋯	-11.445890	-11.679262	-11.955742	-14.325696	-9.868891	-11.801624	-13.110146	-13.526240	-13.287712	-13.287712
Streptococcus pseudopneumoniae	-12.145841	-13.28771	-10.871901	-13.28771	-11.068720	-13.287712	-10.870193	-14.436645	-11.242910	-9.733334	⋯	-11.490629	-10.580310	-10.419921	-12.827242	-9.616045	-11.243982	-12.074813	-12.536532	-13.287712	-13.287712
Dolosigranulum pigrum	-6.936388	-13.28771	-16.837685	-13.28771	-13.287712	-5.054401	-13.287712	-13.287712	-16.754662	-16.336548	⋯	-17.286668	-19.780800	-17.237777	-15.843544	-13.287712	-17.331445	-13.287712	-17.340448	-3.507962	-2.143709
Granulicatella adiacens	-11.560879	-13.28771	-8.095586	-13.28771	-8.781294	-13.287712	-8.280524	-11.067411	-9.625379	-8.294179	⋯	-9.380905	-9.657110	-8.994603	-9.199032	-11.647560	-11.361052	-10.036779	-10.504187	-13.287712	-13.287712
Ligilactobacillus salivarius	-9.133017	-13.28771	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-17.947308	-15.258545	⋯	-17.964740	-17.906331	-13.790318	-15.718013	-13.287712	-13.287712	-15.781082	-16.546899	-13.287712	-13.287712
Limosilactobacillus portuensis	-10.120306	-13.28771	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-21.286668	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712
Limosilactobacillus fermentum	-12.145841	-13.28771	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-17.479313	-17.906331	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712
Lactobacillus gasseri	-10.908802	-13.28771	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-16.947308	-16.506473	⋯	-21.286668	-21.365763	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712
Lactobacillus crispatus	-12.252756	-13.28771	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-18.432734	-17.921510	⋯	-18.701706	-19.780800	-16.790318	-13.876711	-13.287712	-15.699177	-13.287712	-13.287712	-13.287712	-13.287712
Enterococcus cecorum	-10.368234	-13.28771	-13.287712	-13.28771	-15.337587	-11.692563	-13.287712	-13.287712	-17.584737	-16.091435	⋯	-16.964740	-19.365763	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712
Staphylococcus epidermidis	-10.429634	-13.24857	-13.287712	-13.28771	-13.287712	-13.287712	-13.287712	-13.287712	-17.295231	-17.091435	⋯	-17.701706	-18.195838	-13.287712	-13.659120	-13.287712	-12.795392	-14.328570	-12.443208	-13.287712	-16.577908
Veillonella parvula	-8.016558	-13.28771	-8.563307	-13.28771	-10.224424	-13.287712	-9.828373	-7.832503	-8.861740	-8.551307	⋯	-6.074970	-6.283489	-7.572279	-6.700277	-9.730172	-7.439510	-9.145221	-8.694430	-13.287712	-12.323667
Veillonella atypica	-9.120306	-13.28771	-6.992881	-13.28771	-5.673436	-13.287712	-5.325469	-8.102371	-5.907409	-7.578818	⋯	-5.699125	-4.303738	-4.497881	-6.462690	-6.158655	-6.120531	-5.916244	-6.406905	-13.287712	-13.287712
Veillonella nakazawae	-8.773287	-13.28771	-7.990823	-13.28771	-9.171006	-13.287712	-8.690870	-8.823776	-8.376368	-9.213768	⋯	-7.616012	-8.039755	-6.396141	-7.212698	-8.228545	-7.174730	-7.847547	-6.833314	-13.287712	-13.287712
Veillonella dispar	-9.493764	-13.28771	-6.493458	-13.28771	-10.215190	-13.287712	-9.676370	-7.903856	-9.467527	-9.753813	⋯	-9.531363	-9.533268	-7.535447	-8.814131	-9.254029	-9.273995	-9.466290	-8.890612	-13.287712	-13.287712
Veillonella sp. S12025-13	-9.631268	-13.28771	-7.841211	-13.28771	-9.396376	-13.287712	-8.898763	-8.839834	-9.188133	-9.717483	⋯	-8.627564	-7.511674	-7.139984	-8.027724	-8.404201	-7.732090	-8.757838	-7.860668	-13.287712	-13.287712
⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋱	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮	⋮
Prevotella intermedia	-11.145841	-13.287712	-9.332866	-13.287712	-9.293193	-13.287712	-8.950162	-8.702311	-8.028231	-8.168665	⋯	-6.842365	-7.359261	-13.814565	-14.495621	-8.473111	-7.542727	-9.745921	-9.570060	-13.287712	-13.28771
Prevotella jejuni	-11.631268	-13.287712	-7.550550	-13.287712	-4.708332	-13.287712	-4.391391	-6.342494	-6.103218	-8.626890	⋯	-5.006967	-6.273171	-9.748111	-10.646551	-4.557139	-4.932408	-7.988720	-8.601230	-13.287712	-13.28771
Porphyromonas gingivalis	-9.686410	-13.287712	-9.551705	-13.287712	-12.541728	-13.287712	-12.735264	-9.396507	-11.343151	-11.029389	⋯	-12.864604	-9.840731	-17.112246	-13.287712	-8.732874	-11.707930	-5.855996	-6.264123	-13.287712	-13.28771
Tannerella forsythia	-10.526931	-13.287712	-11.611273	-13.287712	-11.786413	-13.287712	-11.346222	-12.184505	-10.411477	-12.088620	⋯	-9.259108	-12.233906	-14.430422	-16.602536	-10.483879	-12.681830	-9.539663	-9.706242	-13.287712	-13.28771
Capnocytophaga gingivalis	-11.953196	-13.287712	-12.017506	-13.287712	-14.337587	-13.287712	-13.879654	-8.702688	-10.553764	-8.990773	⋯	-6.597708	-11.852035	-15.609746	-14.981048	-12.382827	-10.522803	-14.899726	-15.632629	-13.287712	-14.38151
Capnocytophaga leadbetteri	-12.368234	-13.287712	-16.193829	-13.287712	-13.922550	-13.287712	-13.604019	-13.257842	-12.103611	-7.852284	⋯	-7.779865	-12.158749	-13.287712	-13.287712	-14.622293	-15.746483	-13.287712	-13.287712	-13.287712	-13.28771
Fusobacterium nucleatum	-10.953196	-13.287712	-10.607664	-13.287712	-10.510333	-13.287712	-10.077733	-8.781213	-9.727448	-10.072540	⋯	-6.659647	-9.183989	-13.708524	-15.215513	-10.276519	-9.512544	-9.743607	-8.734598	-13.287712	-12.93405
Treponema denticola	-11.783271	-13.287712	-12.566222	-13.287712	-13.398988	-13.287712	-13.879654	-13.693680	-13.207768	-11.869848	⋯	-12.628457	-13.089638	-15.839228	-13.287712	-11.928032	-14.463549	-14.920485	-14.999411	-13.287712	-13.28771
Homo sapiens	-8.543805	-8.619849	-11.106366	-8.624113	-10.524518	-9.078745	-11.061492	-13.535107	-11.713003	-11.803723	⋯	-13.199205	-13.577860	-11.089878	-12.138069	-10.612309	-10.790736	-12.738991	-12.505872	-8.595425	-12.74502
Aspergillus fumigatus	-11.705269	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-20.286668	-21.365763	-13.287712	-16.055048	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Human gammaherpesvirus 4	-12.368234	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio kanaloae	-13.287712	-6.955950	-8.549973	-13.287712	-7.953403	-13.287712	-10.520251	-13.287712	-11.160338	-14.025346	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-9.099603	-13.287712	-13.790605	-13.287712	-6.686070	-13.28771
Vibrio plantisponsor	-13.287712	-8.240753	-9.782402	-13.287712	-9.294408	-13.287712	-11.588422	-13.287712	-12.441779	-16.003973	⋯	-13.287712	-21.365763	-14.254265	-13.287712	-10.472546	-13.287712	-15.356584	-13.287712	-8.047937	-13.28771
Vibrio toranzoniae	-13.287712	-11.187172	-13.179473	-13.287712	-12.612694	-13.287712	-13.287712	-13.287712	-15.469260	-17.769507	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-14.091779	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio diabolicus	-13.287712	-12.017247	-14.411420	-13.287712	-13.259585	-13.287712	-13.287712	-13.287712	-16.947308	-13.287712	⋯	-20.286668	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio alginolyticus	-13.287712	-11.865244	-13.930794	-13.287712	-12.553316	-13.287712	-13.287712	-13.287712	-15.625379	-13.287712	⋯	-19.286668	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio cholerae	-13.287712	-11.602209	-13.488957	-13.287712	-13.167662	-13.287712	-13.287712	-15.991860	-15.710268	-17.390996	⋯	-17.038741	-14.117835	-13.287712	-13.287712	-13.488438	-15.129811	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio ziniensis	-13.287712	-13.379817	-14.361951	-13.287712	-13.726152	-13.287712	-13.287712	-13.287712	-16.362345	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-15.792218	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio crassostreae	-13.287712	-13.187172	-15.030330	-13.287712	-14.752625	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-21.286668	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio celticus	-13.287712	-13.248572	-16.252722	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-17.947308	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Vibrio cyclitrophicus	-13.287712	-13.602209	-15.708402	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Pseudoalteromonas prydzensis	-13.287712	-7.880350	-9.568558	-13.287712	-8.914121	-13.287712	-11.294691	-13.287712	-11.906040	-14.806033	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-10.039002	-13.287712	-14.879262	-13.287712	-7.479948	-13.28771
Pseudoalteromonas rhizosphaerae	-13.287712	-9.617316	-11.396816	-13.287712	-10.752625	-13.287712	-13.604019	-13.287712	-13.847772	-15.632004	⋯	-13.287712	-21.365763	-13.287712	-13.287712	-11.915701	-13.287712	-16.859084	-13.287712	-9.751544	-13.28771
Pseudoalteromonas sp. KAN5	-13.287712	-11.663610	-13.708402	-13.287712	-13.115195	-13.287712	-13.287712	-13.287712	-15.545209	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-13.563400	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Pseudoalteromonas mariniglutinosa	-13.287712	-10.674102	-13.260256	-13.287712	-12.409480	-13.287712	-13.287712	-13.287712	-15.754662	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-13.050751	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Idiomarina loihiensis	-13.287712	-12.817938	-14.345832	-13.287712	-13.952923	-13.287712	-13.287712	-13.287712	-17.169700	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-14.934237	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Pseudomonas aeruginosa	-13.287712	-10.128278	-12.760869	-13.287712	-13.287712	-6.977069	-13.287712	-14.865103	-15.710268	-14.521580	⋯	-19.701706	-16.558408	-13.631119	-9.476427	-12.192306	-12.005915	-13.287712	-13.287712	-13.287712	-13.28771
Pseudomonas sessilinigenes	-13.287712	-10.841397	-13.497835	-13.287712	-12.388571	-13.287712	-13.287712	-13.287712	-13.287712	-13.287712	⋯	-13.287712	-13.287712	-13.287712	-13.287712	-12.838022	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771
Pseudomonas putida	-13.287712	-12.865244	-13.942867	-13.287712	-13.576775	-13.287712	-13.287712	-15.773680	-15.800466	-14.665171	⋯	-17.964740	-16.195838	-9.516678	-11.033849	-13.934237	-13.687589	-13.287712	-13.287712	-13.287712	-13.28771
Acinetobacter sp. TTH0-4	-13.287712	-12.017247	-15.004795	-13.287712	-14.378229	-13.287712	-13.287712	-13.287712	-18.432734	-13.287712	⋯	-21.286668	-13.287712	-13.287712	-13.287712	-14.934237	-13.287712	-13.287712	-13.287712	-13.287712	-13.28771

options(repr.plot.width=20, repr.plot.height=15)

abun_wild_taxon %>%
 column_to_rownames(var="taxon_name") %>%
 head(100) %>% mutate_if(is.numeric, ~ifelse(abs(.) == 0,0.0001,.)) %>%
 mutate_if(is_double,log2)%>%
heatmaply(
    k_col = 2, k_row = 2, xlab="Samples", ylab="taxa",grid_gap=.1,
    colors=colorRampPalette(c('white','orange','red'))(50),
    main="Oral microbiome diversity in COVID+/- patients",
    key.title='Abundance',
    plot_method='plotly') %>%
layout(height=1000, width=1000)

Warning message:
“Specifying width/height in layout() is now deprecated.
Please specify in ggplotly() or plot_ly()”